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Research ArticleA Localization Based Cooperative Routing Protocol forUnderwater Wireless Sensor Networks

Nadeem Javaid1 HammadMaqsood1 Abdul Wadood2 Iftikhar Azim Niaz1

Ahmad Almogren2 Atif Alamri2 andManzoor Ilahi1

1COMSATS Institute of Information Technology Islamabad 44000 Pakistan2Research Chair of Pervasive and Mobile Computing College of Computer and Information Sciences King Saud UniversityRiyadh 11633 Saudi Arabia

Correspondence should be addressed to Nadeem Javaid nadeemjavaidqaugmailcom

Received 4 December 2016 Revised 14 March 2017 Accepted 27 March 2017 Published 30 May 2017

Academic Editor Yujin Lim

Copyright copy 2017 Nadeem Javaid et alThis is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Localization is one of the major aspects in underwater wireless sensor networks (UWSNs) Therefore it is important to knowthe accurate position of the sensor node in large scale applications like disaster prevention tactical surveillance and monitoringDue to the inefficiency of the global positioning system (GPS) in UWSN it is very difficult to localize a node in underwaterenvironment compared to terrestrial networks To minimize the localization error and enhance the localization coverage of thenetwork two routing protocols are proposed the first one is mobile autonomous underwater vehicle (MobiL-AUV) and the secondone is cooperative MobiL (CO-MobiL) In MobiL-AUV AUVs are deployed and equipped with GPS and act as reference nodesThese reference nodes are used to localize all the nonlocalized ordinary sensor nodes in order to reduce the localization error andmaximize the network coverage CO-MobiL is presented in order to improve the network throughput by using the maximal ratiocombining (MRC) as diversity technique which combines both signals received from the source and received from the relay atthe destination It uses amplify-and-forward (AF) mechanism to improve the signal between the source and the destination Tosupport our claims extensive simulations are performed

1 Introduction

In recent years UWSNs are getting more attention due touseful applications such as military surveillance oil explo-ration and seismic and environmental monitoring TheUWSN consists of sensor nodes which are deployed insidethe water The main task of these sensor nodes is to sense theunderwater environment and transmit the sensed data to theonshore sink by using acoustic signals At the same timelocalization is one of the major issues in UWSNs [1] espe-cially in the design of the routing protocol Due to harshunderwater environments data must be gathered with thelocation informationTherefore a sensor nodemust know itslocation at the time of deployment to recover the data fromthe exact locations Although in manual deployment sensornodes know their exact location however due to dynamicnature of underwater manual deployment is not feasible In

this case sensor nodes are randomly deployed in order tocollect the information from the areas which are difficultto reach Localization is very important in many applica-tions like a battlefield area catastrophic areas and so onDue to water currents localization is a challenging task inUWSNs Generally acoustic waves are used in underwatercommunication these waves have high propagation delayand extremely low bandwidth which lead to high probabilityof localization error Unlike terrestrialWSNs the underwaternetwork does not support GPS for position estimationThusefficient localization schemes are needed to estimate theposition(s) of the node(s)

Nowadays cooperative communication has gainedmuchattention in UWSNs due to its unique ability of joining erro-neous packets at the destination by using cooperative diver-sity techniques While minimizing the energy consumptionwith fewer retransmissions a cooperative process involves

HindawiMobile Information SystemsVolume 2017 Article ID 7954175 16 pageshttpsdoiorg10115520177954175

2 Mobile Information Systems

Ordinary sensor node

Anchor nodes

Nodes_Outside_Transmission_RangeA㰀

A㰀

A㰀

A㰀

A㰀

A㰀

A㰀

Figure 1 Anchor nodes coverage problem

the neighboring nodes to relay the data of a particular sourcenode to the destination The main techniques used to relaydata from the source node to the destination node are AF anddecode-and-forward (DF) In the AF relaying technique therelay node amplifies the received signal and then transmitsthe amplified version of the signal towards the destinationwhereas in the DF scheme the relay node decodes thereceived signal and then transmits the signal to the intendeddestination

After the localization the next objective is data routingFor this purpose various attempts in the literature have beenproposed In MobiL [2] anchor nodes deployed on watersurface are used as reference nodes for the localization ofordinary nodes However nodes that are not in the transmis-sion range of these anchor nodes are localized as shown inFigure 1 The nodes with label A1015840 are not in the transmissionrange of anchor nodes which results in higher chance ofthe localization error The anchor nodes do not provideenough coverage to localize the nodes So the remainingnonlocalized nodes will make reference to the other ordinarynodes resulting in a high localization error

To encounter these problems two localization routingschemes are proposed in this paper (i) MobiL-AUV [3] andCO-MobiL InMobiL-AUV three mobile AUVs are deployedunderwater at predefined depth (119889) The mobile AUVs accel-erate towards the surface to find their own three-dimensionalcoordinates via a GPS satellite and dive back to the under-water as shown in Figure 2 The mobile AUVs cover a largenetwork volume and act as reference nodes for nonlocalizednodes minimizing the localization error due to minimumdistance between mobile AUVs and nodes

We also present a region based cooperative routingmech-anism as shown in Figure 3 The nodes closer to the onshoresink (nodes in transmission range of sink) are considered inregion one and the rest of the nodes are considered in region2 Nodes in region 1 directly communicate with the sinkconsuming less energy On the other hand nodes in region2 communicate via a cooperatively chosen best relay


Mobile AUV

Figure 2 AUVs coverage area

Sink Base station

D

R

S

R1

R2

Figure 3 Region base cooperation

The remainder of the paper is organized as follows Therelated existing work is summarized in Section 2 Section 3discusses our scheme in a detail Then simulation resultsare presented and discussed in Section 4 and finally Sec-tion 5 concludes our work by discussing the findings of ourschemes

2 Related Work

In this section we discuss recent routing protocols forUWSNs in two categories (i) nodes mobility and localizationbased and (ii) cooperation based

21 Node Mobility and Localization In [4] the authorspropose a distributed localization technique for UWSNsTheauthors introduce two types of nodes anchor nodes andordinary nodesThe anchor nodes are used as reference nodeswhich are localized whereas the ordinary nodes do not knowtheir location The main focus is on the localization ofordinary nodes by using distributed localization techniques

Mobile Information Systems 3

The authors in [5] propose a centralized localizationtechnique in which each sensor node sends its location infor-mation to the onshore sink The scheme results in a higherenergy utilization as well as a high localization error Thecentralized localization schemes are not suitable for a highlevel UWSN task

Performance analysis of ranged base and distributedlocalization techniques and protocols are presented in [6]The authors conclude that the existing protocols that aremade for small scale networks cannot be used in large scalenetworks

Received signal strength (RSS) and ad hoc on-demanddistance vector protocol to detect the attacks on the localiza-tion mechanism is proposed in [7] The authors choose thebest and secured neighbors for data forwarding process suchthat data is transmitted through the qualified secured neigh-bors

The authors in [8] propose correction received signalstrength index (RSSI) localization scheme for UWSNs Thereference nodes send beacon message on receiving a mes-sage the nodes use median mean filtering to process theinformation and by the help of weighted centroid techniquethe unknown node finds its three-dimensional coordinates

Optimization and minimum cost factor is brieflyexplained in [9] The authors focus on localizing the nonlo-calized nodes by utilizing lower number of anchored nodesTo efficiently use the anchor nodes the authors proposethe greedy mechanism to select the anchor nodes pair Thisscheme also introduces the confidence interval methodologyto handle the localization error issues

In [10] multihop localization process is proposed Thisscheme has two phases in the first phase the nodes find theshortest link between anchored nodes and ordinary nodes byusing a greedy algorithm In the second phase the nonlo-calized nodes find their positions by using trilaterationscheme

The time difference of arrival (TDOA) based localizationtechnique for a heterogeneous network is proposed in [11] Inthis scheme there are three types of nodes the target nodesthe anchored nodes and the reference nodes In the first stepthe TDOA of minimum four nodes sets is calculated and inthe second step the valueswith position information of locali-zed nodes are used to find the position of the target nodes

The authors in [12] propose a scalable localization tech-nique The protocol has two phases anchored node local-ization and nonlocalized node localization On the basis ofnodersquos past mobility the nodes predict their future positionDuring anchor nodes localization the anchor nodes use thelateration technique to find their respective coordinates

In [13] the authors present three different deploymentstrategies and briefly explain their effects on localizationThe authors conclude that tetrahedron deployment strategyshows good results as compared to other deployment strate-gies in terms of the localization error

An analysis of localization process is proposed in [14]The authors make use of asynchronous clock to make anchornodes asynchronous The asynchronous anchor nodes help

other nodes to find their position in an effective way with lesslocalization error

Localization mechanism for nonlocalized nodes is dis-cussed in [15] The protocol consists of two parts in the firstpart sensor nodes estimate their distance from the anchoredreference node and in the second part sensor nodes utilizetheir estimated distance to find their coordinates with atrilateration mathematical technique

The authors [16] propose a hybrid localization scheme forocean sensor networks This localization scheme is dividedinto three steps in the first step the group nodes arelocalized to act as anchor nodes in the second step withthe help of anchor nodes the nonlocalized nodes find theircoordinates to become localized and in the final step the freedrifting nodes find their location by applying floating nodelocalization algorithm (FLAP)

In [26] a network access mechanism is presented in threephases (i) network discovery (ii) finding of a relay path and(iii) association for multihop underwater acoustic local areanetwork It achieved the network lifetime high packet deliv-ery ration with the balanced energy consumption

Wu et al [27] propose a network coding based routingprotocol for UWSNs In this scheme the authors presentthree algorithms (i) time-slot based routing (TSR) to reducethe sensor nodes conflict due to underwater dynamic nature(ii) time-slot based balanced routing (TSBR) in order tominimize the energy consumption and (iii) time-slot basedbalanced network coding algorithm to balance the energyconsumption over long routing paths

An energy efficient depth based routing protocol is pro-posed in [28] It considers a low depth sensor node that hashigh residual energy to transmit a data packet to maximizethe network lifetime It performs better in dense deploymenthowever in sparse conditions it consumes more energyresulting in low network lifetime and lower packet deliveryratio

Authors in [29] propose an energy efficient routingprotocol based on a physical distance and a residual energy(1198641198771198752119877) for UWSNs 1198641198771198752119877 uses physical addresses ofnodes to minimize the location error It also enhanced thenetwork lifetime with balanced energy consumption

An energy efficient routing algorithm for UWSN inspiredby ultrasonic frogmechanism is presented in [30] In order toimprove the network lifetime it utilizes the gravity functionto indicate the attractiveness of network nodes for each otherThis scheme achieves comparatively a high network lifetimeand more packet acceptance ratio

Cao et al propose a balanced transmission algorithmfor UWSNs [31] Authors divide the transmission into twophases (i) an energy efficient algorithm based on the optimaldistance to optimize the energy consumption of the networkand (ii) data load algorithm which balances the data load onthe sensor nodesThis protocol achieves the energy efficiencyby balancing the data load The comparison of the discussedrouting protocols (Node Mobility and Localization) is givenin Table 1


Table 1 State-of-the-art related work Node Mobility and Localization

Technique Features Achievements Limitations

MobiL a 3-dimensional localizationscheme for mobile UWSNs [2]

Handles nodes mobility andnodes localization

Mobility model for mobilenodes efficient node localization

with less error

Large distance betweenordinary nodes and referencenodes resulting in localization

errorDesign and implementation of atime synchronization-freedistributed localization [4]

Event-driven timesynchronization-free distributed

localization scheme

Successful efficient nodeslocalization

ToA based distance estimationmethod is used which causes

error if delay occurs

A survey of architectures andlocalization techniques for UASNs[5]

Survey of UASNs andlocalization techniques

Briefly explaining the existinglocalization techniques and their

drawbacks

Performance analysis ofdifferent localization methodswith different mobility models

is neglectedPerformance evaluation oflocalization algorithms in large scaleunderwater sensor networks [6]

Comparison of ranged base anddistributed localization schemes

Analysing different schemes andexplaining briefly their

advantages and disadvantages

Analysis of differentlocalization methods is not

performedLocalization using multilaterationwith RSS based randomtransmission directed localization[7]

RSS based efficient randomtransmission directed

localization is introduced

RSS is used for distanceestimation multilateration

technique is used for efficientnodes localization

RSS greatly is affected bychannel conditions

A distance measurement wirelesslocalization correction algorithmbased on RSSI [8]

Node localization mechanismbased on RSSI

Efficient correction of estimatedRSSI values efficient measuringof the coordinates of nodesminimizing error during

localization process

RSSI does not accuratelylocalize nodes due to

multipath propagation andfading effects

Minimum cost localization problemin three-dimensional ocean sensornetworks [9]

Minimum localization cost andhandles distance problem

Finding best anchor set tomeasure each node coordinate

efficiently

If confidence intervalthreshold increases the anchor

nodes selection will beaffected

A multihop localization algorithmin UWSNs [10]

Multihop localization algorithmto handle the void nodelocalization problem

Efficient mechanism for nodeslocalization

Not suitable for large scaleapplications

TDOA based target localization ininhomogeneous UWSNs [11]

TDOA based localizationscheme introduced forinhomogeneous WSNs

Achieving improved localizationcoverage area

Affected by channelconditions time

synchronization is veryimportant

Scalable localization with mobilityprediction for UWSNs [12]

Localization scheme for largescale applications with mobility

forecasting

Efficient node mobilityprediction and improved

localizationHigh energy consumption

Impacts of deployment strategies onlocalization performance in UASNs[13]

Efficient node deploymentstrategies and their effects onlocalization coverage area and

error are introduced

Successfully achieving largercoverage area and less errorbecause of efficient nodedeployment mechanism

Localization is not veryaccurate

On-demand asynchronouslocalization for UWSNs [14]

On-demand nodes localizationscheme using asynchronous

anchor nodes

Successfully localizing both typesof nodes passive and active

Passive nodes localizationaccuracy is less than the active

nodesA three-dimensional localizationalgorithm for UASNs [15]

Iterative and distributed nodeslocalization algorithm

Improved coverage area with lesserror

When node mobility increasesthe localization error increases

Localization for drifting restrictedfloating ocean sensor networks [16]

Efficient nodes localizationscheme

Large number of nodes findingtheir three-dimensionalcoordinates successfully

Higher network deploymentcost

In the discussed existing routing protocols the impactof nodes mobility is not taken into account which results inhigh localization error and degrades the performance of thenetwork Therefore to mitigate the localization error due towater currents in our proposedwork the speed of the node iscomputed in order to estimate the coordinates of the sensor

node deployed in the network field The details of procedureare given in Section 31

22 Cooperative Routing The authors in [17] propose anenergy efficient cooperative routing protocol It is a crosslayer protocol for cooperative communication where if the


destination node fails to receive the data packet successfullythen the nearby relay node retransmits the data packet to thedestination node This protocol achieves energy efficiencycompared to its counterpart schemes

A cross layer cooperative communication protocol isproposed in [18]The authors utilize the power allocation androute selection information during the route selection phasea link with minimum chances of collision is selected forthe data transmission This protocol achieves high networkthroughput however the mechanism of forwarder selectionis not reliable

An incremental qualified relay selection for the coopera-tive communication is presented in [19] When the destina-tion node fails to receive the data via direct transmission therelay node was used to retransmit the same data packet Theauthors computed closed form expressions for bit error rate(BER) and outage probability It achieves less probability oferror and high network throughput at the cost of high energyconsumption

In [20] the authors propose an efficient cooperative rout-ing protocol In this technique the selection of the best relaydepends on the channel conditions and distance betweenthe source node and the neighbor node The best relay isselected from the set of qualified neighboring nodes Theacknowledgement mechanism helps to reduce the redundantpackets resulting in high reliability however the relay selec-tion mechanism is not energy efficient

Authors in [32] propose an energy efficient routing proto-col for cooperative transmission Two problems are tackled inthis proposed scheme the first one is the energy consumptionand the other one is the power allocation for cooperativetransmissions This scheme mainly focuses on the distancebetween different nodes for efficient power allocation

A cooperative routing protocol for UWSNs is proposedin [33] There are three types of nodes the source nodesthe relay nodes and the destination nodes When the data istransmitted from the source to the destination if the destina-tion node fails to receive error-free data then the relay nodehas to retransmit the data towards the destination There aretwo scenarios in the first scenario single relay node is selectedwhereas in the second scenario two relay nodes participate inthe data retransmission

In [21] a cooperative routing protocol is presented tominimize the collision in the network Authors formulatedthe problem with the use of mixed integer nonlinear pro-gramming (MINLP) They used branch-and-bound algo-rithm to reduce the search space and save the energy forsolving mixed integer nonlinear programming problems

To achieve energy efficiency the authors in [22] proposea scheme which allocates a power at each hop between thesender and the receiversink Based on the allocated powereach sensor node computes its signal-to-noise ratio (SNR) ofthe link (between the source and the destination) and dis-tance between the source and the destination It performsbetter in terms of network lifetime and end-to-end delay

In [23] the authors present a cooperative strategy for datatransmission in a clustered networkThey divided the scheme

hello packet transmission into two phases (i) interclusterand (ii) intracluster In intercluster the cluster head (CH)broadcasts the data packet directly to the neighbor CHs andvia potential relay nodes only if any CH is not in its trans-mission range Similarly in intracluster the CH forwards itsdata packets to all sensor nodes within the cluster the nodeswhich receive hello packet successfully selected as poten-tial relay nodes However it consumes more energy whenthe nodes density is high in a cluster

Authors propose a cooperative routing algorithm in [24]This algorithm considers a propagational delay and BER ofthe link to select the best incremental relay for data for-warding between the source and the destination However itachieves high performance of the network at the cost of moreend-to-end delay

To improve the network throughput a cooperativescheme is presented [25] This scheme uses partner nodesmechanism for cooperation and for the selection of eachnode SNR of the link and propagational is checked if the linkmet the criteria then a node is elected as a partner node to per-form cooperationHowever this scheme enhanced the packetdelivery ratio with higher stability period at the cost of highenergy consumption Summary of the cooperative routingschemes is presented in Table 2

In this subsection numerous cooperative routing algo-rithms are stated The energy consumption is high due toduplicate packets at the destination in the discussed schemesdue to energy constraint of sensors in this paper we have pro-posed a CO-MobiL in which relay node only transmits datapacket towards the respective destination when the receivedpacket is erroneous or not received by the destinationTheworkingmechanismof the proposedwork is given in Sec-tion 32

3 Proposed Work

In this paper two contributions are presented (i) an AUVbased node localization scheme (MobiL-AUV) and (ii) acooperative routing protocol (CO-MobiL) In the first non-localized nodes are localized by using an efficient AUV aidedlocalization mechanism In the second scheme after thesuccessful localization of node regions based cooperative datarouting is carried out Details are as follows

31 MobiL-AUV We consider a three-dimensional under-water network where 119899 numbers of sensor nodes are ran-domly deployed With the help of onboard pressure sensorssensor nodes are capable of determining their depth Allnodes can communicate with mobile AUV as well as withother deployed nodes We assume that 119873 is the number ofmobile AUVs that are deployed inside the water at depth 119889These mobile AUVs periodically accelerate towards the watersurface to get their own three-dimensional coordinates infor-mation by using the GPS [34 35] After getting the requiredinformation these dive back into the water and broadcastlocalization beacon messages These mobile AUVs act asreference nodes for all other underwater nodes


Table 2 State-of-the-art related work cooperative routing

Technique Features Achievements LimitationsJoint cooperative routing and powerallocation for collisionminimization in WSNs withmultiple flows [17]

Cooperative routing protocoloptimal power allocation to sensor

nodes

Collision probability isminimized High computational cost

Energy efficient cooperativecommunication for datatransmission in WSNs [18]

Reliable and efficient datacommunication cooperative routing

protocol

High throughput and reliabledata delivery

Mobility of sensor node isneglected qualified

forwarder node selectionmechanism is not accurate

Performance analysis of cooperativediversity withincremental-best-relay techniqueover Rayleigh fading channels [19]

Incremental relaying cooperation isimplemented

Less probability of error higherthroughput and reliability High energy consumption

Exploiting cooperative relay forreliable communications in UASNs[20]

Cooperative scheme that increasesthe throughput and reliability of the

networkHigh network throughput Nonefficient relay node

selection mechanism

Optimal and near-optimalcooperative routing and powerallocation for collisionminimization in WSNs [21]

MINLP problems are solved withbranch-and-bound algorithms

Minimizing the end-to-end delayby reducing the search space

Only efficient forpredefined network

topologies

Co-UWSN cooperative energyefficient protocol for UWSNs [22]

Incremental relay is selected on thebasis of distance and SNR of the link

Comparatively less energyconsumption

ACK on each packetresulted in high end to

delayEECCC (energy efficientcooperative communication inclustered WSNs) [23]

Clustering and cooperativecommunication in the network

Comparatively less energyconsumption with direct

communication

High energy consumptionin dense deployment due toredundant transmissions

Relay selection and optimizationalgorithm of power allocation basedon channel delay for UWSNs [24]

Relay is selected on the basis of BERand propagational delay Improving the network lifetime High end-to-end delay

Cooperative partner nodes selectioncriteria for cooperative routing inUWSNs [25]

Partner node selection on the basisof depth threshold andpropagational delay

Comparatively high packetacceptance ratio High energy consumption

All the ordinary sensor nodes have a communication linkwithmobile AUVs and alsowith other sensor nodes deployedunderwater The mobile AUVs form a link with GPS satellitevia radio waves and the use acoustic waves to establish a linkwith underwater nodes There are two phases in the MobiL-AUV localization scheme

(1) Mobility forecasting(2) Localization process

(1) Mobility Forecasting In mobile UWSN water currentshave a strong impact on the mobility of sensor nodes Forthe sake of simplicity we only focus on 119909 and 119910 coordinatesWe ignore the 119911 coordinate because two distinct coordinates(points) always compute a straight line between the sourceand the destination in the given transmission range In thiscase a straight data path must be established between thesender and the receiver node to avoid the use of extraenergy Considering an underwater scenario the node 119896at depth 119889 experienced underwater current velocity V119896 =(V119909119896(119889) V

119910

119896(119889) 0) where V119909119896 and V

119910

119896are the velocities of the node

in 119909 and 119910 directions respectively Due to spatial correla-tion in underwater networks mobile sensor nodes show a

group-like behavior [2] So by using the group movementproperty as shown in (1) we can find the velocity of the node

V119909119896 (119889) =119899neigh

sum119898=1

119877119898119896V119909119898 (119889)

V119910119896 (119889) =

119899neigh

sum119898=1

119877119898119896V119910119898 (119889)

(1)

In (1) 119899neigh represents the number of neighbors of sensornode 119896The Euclidean distance between node119898 and node 119896 ispresented as 119903119898119896 and119877119898119896 = (1119903119898119896)sum

119899neigh119898=1 (1119903119898119896) represent

the interpolation coefficientAfter the velocity estimation each ordinary node in the

network interchanges the speed beacon message periodicallywith other nodes These special beacon messages carry thespeed information of respective node By utilizing the speedinformation of a neighboring node every ordinary node inthe network can predict its mobility pattern

(2) Localization Process After the mobility prediction ofordinary nodes the process of localization starts During thislocalization process the mobile AUVs broadcast localization


T1 T2 T3

(xd1 yd1 zd1) (xd2 yd2 zd2) (xd3 yd3 zd3)

(xd yd zd) (xd㰀 yd㰀 zd㰀) (xd㰀㰀 yd㰀㰀 zd㰀㰀)

AUV_1 AUV_2 AUV_3

KKKK K

Figure 4 MobiL-AUV localization process

beacon message to the ordinary nodes The ordinary sensornodes listen to these beacon messages On receiving the bea-con messages all the nodes estimate their distance from themobile AUV by using an efficient measurement techniqueAs shown in Figure 4 the ordinary sensor node 119896 initially atposition (119909119889 119910119889 119911119889) listens to the localization beacon mes-sage At 1198791 from amobile AUV located at (1199091198891 1199101198891 119911d1) theordinary node calculates the distance with respect to themobile AUV by using the following equation [9]

Distance (119889119896) = (119879send minus 119879recv) times 119881 (2)

where 119879send is the time when the mobile AUV broadcaststhe localization beacon message 119879recv is the time when thesensor node receives the beacon message and 119881 is the speedof sound in an underwater environmentThe above process isrepeated at 1198792 and 1198793 until the ordinary nodes receive bea-con messages from 119899AUV different mobile AUVs The flow oflocalization process is shown in Figure 5

By substituting values of velocity (V119909119896(119889) V119910

119896(119889)) in (3) we

can estimate the values of (1199091198891015840 1199101198891015840) and (11990911988910158401015840 11991011988910158401015840)

1199091198891015840 = 119909119889 + (1198792 minus 1198791) times V119909119896 (119889)

11990911988910158401015840 = 1199091198891015840 + (1198792 minus 1198791) times V119909119896 (119889)

1199101198891015840 = 119910119889 + (1198792 minus 1198791) times V119910119896 (119889)

11991011988910158401015840 = 1199101198891015840 + (1198792 minus 1198791) times V119910119896 (119889)

(3)

Here in (3) (119909119889 119910119889 119911119889) (1199091198891015840 1199101198891015840 1199111198891015840) and (11990911988910158401015840 1199101198891015840101584011991111988910158401015840) are the coordinates of node 119896 and (1199091198891 1199101198891 1199111198891)(1199091198892 1199101198892 1199111198892) and (1199091198893 1199101198893 1199111198893) are the coordinates ofmobile AUVs at times 1198791 1198792 and 1198793 respectively Bysubstituting values in (4) a node can estimate its position

(119909119889 minus 1199091198891)2 + (119910119889 minus 1199101198891)2 + (119911119889 minus 1199111198891)2 = 11988921

(1199091198891015840 minus 1199091198892)2+ (1199101198891015840 minus 1199101198892)

2+ (1199111198891015840 minus 1199111198892)

2= 11988922

(11990911988910158401015840 minus 1199091198893)2+ (11991011988910158401015840 minus 1199101198893)

2+ (11991111988910158401015840 minus 1199111198893)

2= 11988923

(4)

No

Yes

Anchor nodes find positioncoordinates (3)

End

MobiL-AUVsBroadcast location beacon

Sensor node listens to beacon

Receiving beacon messageBeacon = + 1

Start

deployment

Mobility prediction

Sensor nodes amp mobile AUVs

message

beacon

If == 3beacon

Figure 5 Flow chart of complete localization process

32 CO-MobiL After the process of mobility and localiza-tion the process of data routing starts For routing purposesresearchers have proposed different routing protocols [17ndash20] In our proposed scheme the source nodes broadcast


D

D

S

S

Rb

Rb Best relay node

Destination node

Direct path

Source node

Through relay

Ysd=Hs

lowastg sd

+n sd

Ysr= Hs lowast

gsr+ nsr

Y rd=Y srlowastg rd+n rd

Figure 6 Network model

data packets towards the destination If the destination failsto receive the error-free packet then the best selected relaynode will transmit data packet to the destination At the des-tination theMRC is used as a diversity combining techniqueThe relaying technique we used in our scheme is amplify-and-forward

The underwater environment is harsh due to whichthe transmitted signals experience the noise the multipathfading and the interference Every link from the source to thedestination and from the relay to the destination is affectedby the Rayleigh fading and additive white Gaussian noise(AWGN) The Rayleigh fading scatters the acoustic signalbefore its arrival at the destination because of less dominantpropagation towards the destination and AWGN is used tosimulate the background ambient noise of the channel

The signal transmitted from the source node to thedestination and the relay node to the destination is shown inFigure 6Thedata packets are transmitted to both the destina-tion and the relay node If the source node fails to receive anerror-free packet then the relay node transmits the same datapacket from the alternative path to the destination where theMRC diversity technique is used to combine the data packetsto get the error-free packet Its mathematical expression isgiven in (5) (6) and (7)

119884119904119889 = 119867119904 times 119892119904119889 + 119899119904119889 (5)

where119884119904119889 is the directly transmitted signal from the source tothe destination119867119904 denotes the channel from the source nodeto the destination nodesink 119892119904119889 represents the broadcastinformation between the source and the destination and 119899119904119889shows the ambient noise added to channel119867119904

119884119904119903 = 119867119904 times 119892119904119903 + 119899119904119903 (6)

119884119904119903 denotes the transmitted signal between the source andthe relay as shown in Figure 6 119892119904119903 shows the informationtransmitted by the source to the relay Similarly 119899119904119903 is theambient noise added to channel119867119904

119884119903119889 = 119884119904119903 times 119892119903119889 + 119899119903119889 (7)

When the destination fails to receive data packets from thesource node then relays transmit data packets according

to (7) where 119884119903119889 is the transmitted data from the relay tothe destination119892119903119889 denotes the information forwarded by therelay to the destination and 119899119903119889 represents the noise added tothe information 119884119904119903 on the channel119867119904

There are two phases in CO-MobiL protocol

(1) Initialization phase(2) Data forwarding phase

In the first phase nodes are deployed and each node finds itsqualified relay and destination This information is used inthe second phase to transmit data from source to destinationThe flow chart of CO-MobiL is shown in Figure 7

(1) Initialization Phase In this phase nodes are randomlydeployed underwater Each node in the network finds aqualified relay node and destination for data transmission

(i) Relay SelectionThe relay selectionmechanism is shown inAlgorithm 1 All nodes in the network broadcast hello packetwithin their transmission range the hello packet format isshown in Figure 8 On receiving the packet each node sends aresponse packet to the nodes from which they receive a hellopacket A response packet is shown in Figure 9 it containsinformation about the node ID depth residual energy andSNR of each node in the network On receiving the responsemessage each node computes the weight function to find thequalified relay node in the networkThe relay is selected basedon the following parameters SNR residual energy (RE)depth of a node (119863119894) and delay (119879delay) between the sourcenode and the relay node Each node maintains its neighborinformation to gather data from the source node and thenfrom these neighbors a relay node is selected on the basis of amaximumweight functionTheweight function of each nodeis computed as given in

119882weight =RE times SNR119863depth times 119879delay

(8)

(ii) Destination Selection The destination node is selected onthe basis of depth and residual energy A node with higherresidual energy which lies outside the depth threshold (119863119889th)but within the transmission range (119879range) of the source nodeis a qualified destination ((119879range) ge 119889119894 ge 119863119889th) Figure 10shows the destination node selection mechanism 119863119889th iscomputed according to119863119889th = 119889119894 minus1 where 119889119894 is the depth ofany node of the networkThe objective of119863119889th is to minimizethe number of hops to reduce the energy consumption Theweight function presented in (9) has been used to find thedestination for a particular source node

119882weight =RE119889119894

(9)

(2) Data Forwarding Phase In this phase the source nodegenerates data packets and forwards these towards the desti-nation and the relay node At the destination node a decisionismade on the basis of instantaneous SNRbetween the sourceand the destination whether the data received from thedirect path is acceptable or a relay will be used for the data


Start

Sensor nodes amp mobileAUVs deployment

Mobility prediction

No

No

Yes

Yes

Node localization

Direct transmissiontowards sink

If node is inregion 1

Node is in region 2

Packet sent todestination amp best relay

Relay transmit packettowards destination

ACK send amp relaydiscard the packet

End

If BER atdestination islArr

threshold

Figure 7 Complete cooperation process

(1) 119878source Source node(2) REenergy Residual energy of node(3) SNR119904119903 Signal to Noise ratio between source and expected relay(4) 119863depth Depth of the node(5) 119879delay Delay between source and expected relay(6) 119878source broadcast control packet(7) Neighboring nodes send response message(8) if Response message received = True then(9) Compute119882weight function using equation (8)(10) end if(11) Node with maximum value of119882weight function is considered best relay

Algorithm 1 Relay node selection


Node ID Residual energy Depth

Figure 8 Control packet format

Node ID Residual energy Depth SNR(Link)

Figure 9 Response packet format

D

S

Depth threshold Transmission range

Figure 10 Destination node selection

retransmission The instantaneous SNR [36] is computedaccording to

120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)

where 120574119860119865 denotes amplify-and-forward signal 120574119904119889 is thechannel instantaneous SNR between the sender and thereceiver and 120574119904119903119889 is the equivalent instantaneous SNRbetween the source and the destination through the relaynode The equivalent instantaneous SNR of the relayeddatasignal is computed as given in

120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)

The network is divided into two regions as shown in Fig-ure 11 The division reduces the energy consumption on thesensor nodes deployed near the sink Due to the cooperationthe number of retransmissions increases at the destinationresulting in more energy consumption In order to mitigatethe energy consumption and to prolong the network lifetimewe have limited the cooperation process in one region andin the second region direct data transmission is carriedout The working mechanism of both regions is discussed inthe following subsections

(i) Direct Transmission Region The nodes closer to theonshore sink (nodes in transmission range of sink) are con-sidered in region one whereas the nodes that are not in thetransmission range of onshore sink are considered in secondregion Nodes that belong to region one forward their datapackets towards the sink via direct transmission As thedistance between the source node and the sink in region one

D

D

S

S

Rb

Rb

Best relay node Destination node

Direct path

Source node

Relay

Sink

Figure 11 Data forwarding scenario

Data

Data

Data

ACKD

S

Rb

Figure 12 Data forwarding mechanism (ACK)

is not very large lower amount of energy is consumed duringdirect transmissions andmoreover the bit error rate (BER) indirect transmission is less compared to multihoping In casethere is no direct communication link between the nodes ofregion 1 and the sink then data forwarding is carried out viacooperation

(ii) Cooperative Region In region two nodes transmit a datapacket towards the destination via cooperation During thecooperation process the source node transmits data packetstowards the destination and the best relay node On receivingthe data packet the relay nodewaits for the acknowledgement(ACK) or negative acknowledgement (NACK) from thedestination node At the destination node BER is computed ifthe BER is less than the BER threshold the packet is acceptedat the destination and ACK is sent The relay node overhearsACK and discards the packet This scenario is shown inFigure 12

If the BER at destination is greater than the defined BERthreshold then NACK is sent and the relay node amplifiesthe received data and transmits the amplified data packets


Data

Data

Data

D

S

Rb

NACK

Figure 13 Data forwarding mechanism (NACK)

towards the destination This scenario is shown in Figure 13At the destination MRC technique is used as a diversitycombining technique The signals from all links from thesource to the destination and from the relay to the destinationare added together to generate an original data packet

Amplify-and-Forward The relaying technique used in theproposed scheme is AF In this technique the source nodesends data packets to the destination using a direct linkif the destination is unable to detect the packets using thedirect link the relay forwards the data to the destinationTherelay amplifies the data and transmits the amplified data todestination

4 Experiments and Discussions

Theperformance of our proposed schemes (MobiL-AUV andCO-MobiL) is validated via simulations We have claimedthat region based cooperative routing minimizes the local-ization error and improves the data delivery ratio comparedto existing traditional localization schemes (eg multihoplocalization three-dimensional localization) Through sim-ulation results we have showed that our schemes performbetter than the existing compared schemes (MobiL andUDB)

The network field is considered of size 500m times 500mtimes 500m number of nodes vary from 50 to 200 withtransmission energy 2 joules (J) and receiving energy of 01 Jand three AUVs are deployed to localize the ordinary nodesThe simulation parameters are given in Table 3 [2]

41 Performance Metrics

(i) Alive nodes they are nodes that have a sufficientamount of energy to transmit a data packet from thesource to the destination

(ii) Dead nodes they are nodes that do not have asufficient energy to transmit data from the source tothe destination

Table 3 Simulation setting parameters

Simulation parameter ValueSensor nodes 50ndash200Network dimension 500m times 500m times 500mLocalization threshold 1mTransmission energy 2 JReception energy 01 JTransmission range 100mTransmission frequency 22KHzNode mobility 1ndash5ms

CO-MobiLACE-SingleRetransmissionACE-DoubleRetransmission

60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round

Figure 14 Alive nodes

(iii) Throughput it means the successfully delivered datapackets at the sink

(iv) Energy consumption it is the total amount of energyconsumed in the network by all nodes

(v) Localization error it is the Euclidean distancebetween the original position of a sensor node(119909119889 119910119889 119911119889) and the estimated position of a sensornode (1199091198891015840 1199101198891015840 1199111198891015840)

(vi) Localization coverage It is the ratio of the numberof successfully localized nodes to the total numberof deployed nodes in the whole network A node issuccessfully localized if its localization error is lessthan a predefined localization error threshold

42 Performance Discussion The alive nodes of all schemesare shown in Figure 14 The results show that our schemeoutperforms the existing techniques there are more alivenodes in our than others as shown in Figure 14 In ACE-DoubleRetransmission scheme [33] two relay nodes are usedfor a data transmission which increase the energy cost Morenodes are involved in a data transmission from the sourceto the destination which results in rapid energy depletion


0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s

ACE-SingleRetransmissionACE-DoubleRetransmissionCO-MobiL

Figure 15 Throughput

of nodes and the network lifetime is decreased In ACE-SingleRetransmission all nodes are involved in cooperationprocess thus the energy consumption of the protocol isgreater whereas in our protocol due to efficient relay selectionthere is no need for the second relay to retransmit data to thedestination The nodes nearer to the sink directly transmitdata to the sink as the distance between the sink and thesenodes is not so large thus avoiding cooperation in the vicinityof the sink is to balance the energy consumption of thenetwork

Figure 15 represents the throughput for all the simulatedschemesThe throughput of our scheme is more as comparedto the other schemes Due to the efficient selection of arelay node a large number of data packets reached theirdestination successfully If the destination fails to receive anerror-free packet from the source then the relay forwardsdata to the destination In the other two schemes the relay isselected on the basis of depth and residual energy The linkbetween the source and the relay is ignored due to whichthe existing schemes experience packet drop and result indecreased throughput whereas in the proposed scheme therelay is selected on the basis of depth residual energy andSNR of the link between the source and the relay Due to thebest selection of the relay a greater number of data packetsare successfully received at the destination By using directtransmission in region 1 (ie closer to the sink) the proba-bility of the BER decreases As a result high throughput isachieved

In Figure 16 the energy consumption for all simulatedschemes is shown In ACE-DoubleRetransmission schemedue to the selection of two relays more energy is con-sumed Whenever multiple relay nodes are used for retrans-missions it results in high energy consumption In ACE-SingleRetransmission scheme all nodes are involved in thecooperation process which increases the energy consump-tion whereas in our proposed scheme the region based coop-eration is introduced Nodes that are far from the onshore

ACE-SingleRetransmissionACE-DoubleRetransmission

0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL

Figure 16 Energy consumption

Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)

100 150 20050Number of nodes

CO-MobiL

Figure 17 Localization error

sink transmit data packets to the destination by cooperativerouting and the other nodes that are part of region one(in the transmission of sink) directly transmit the datapackets to the sink Due to division of the field the distancebetween the nodes of region one and the sink is reducedwhich results in less energy consumption

The effects of localization error are shown in Figure 17During simulations we kept localization threshold 1m Thelocalization error parameter is plotted by varying the numberof sensor nodes from 50 to 200 During the computationof localization error the mobile AUV nodes are kept asidebecause these nodes are already localized With the increasein the communication distance between ordinary nonlocal-ized nodes andmobile AUVs the localization error increasesTo reduce the localization error in proposed scheme mobile


MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB

Figure 18 Localization coverage

AUVs cover the large network volume that results in lesslocalization error

The localization coverage is shown in Figure 18The resultshows that our scheme MobiL-AUV outperforms MobiL [2]and UDB [37] in terms of localization coverage With theincrease in the number of nodes in proposed scheme thelocalization coverage increases up to 80 Our proposedscheme results in less localization error due to which a largenumber of nodes get localized The localization coveragedepends on the transmission range of the reference nodesWith the increase in the transmission range of referencenodes more numbers of nodes get their position coordinatesDue to mobile AUVs the greater number of ordinary non-localized nodes exists in the transmission range that resultsin the successful localization of large number of the ordinarynodes In MobiL reference nodes at the water surface areused to localize the network nodes due to which a minimumnumber of nodes get localized whereas in UDB directionalbeacons are broadcasted which are bounded by angle whichvaries from 10 to 90 degrees Due to the involvement of anglearea of the beacon message is restricted due to which a lowernumber of nodes receive beacon messages resulting in lesslocalization as compared to our proposed localization scheme(MobiL-AUV)

In Figure 19 the localization of the proposed scheme(MobiL-AUV) is presented at numerous time intervals withrespect to node mobility When the node mobility is 1 meterper second (ms) as shown in Figure 19(a) MobiL-AUVbroadcasts beacon message after every 1 second over a prede-fined path to localize the sensor nodesThenormalized valuesare shown in Figure 19(a) the success ratio increases withthe increase in the nodes density from 50 to 200 It canbe clearly seen that when beacon message interval is 1 s (1second) the localization ratio increases as the node densitychanges from 50 to 200 The success ratio at lower interval

(1 s) is more because nodes receive beacon messages moreoften to localize themselves whereas at high intervals (2 s3 s) nodes receive fewer beacons resulting in fewer localizednodes in the network Therefore the success ratio is lowerwhen the value of the time interval is high As it can beseen from Figure 19(b) at 1 s the success ratio is 92 andfor 2 s and 3 s the localization success ratio is 89 and 86respectivelyWhen the nodemobility is 3ms the localizationsuccess slightly decreases because nodes move out of therange from MobiL-AUV As it is shown in Figure 19(b) withthe increase in the node speed the success ratio is affectedSimilarly From Figure 19(c) it further decreases as the nodemoves with the speed of 5ms Therefore we have used (2)to acquire the coordinates of the nodes by considering thespeed of the nodes which gave us high success in estimatingthe coordinates of the nodes

5 Performance Trade-Offs

Trade-offs made in our proposed protocol are given inTable 4 CO-MobiL achieves high network throughput at thecost of energy due to cooperation as shown in Figures 15 and16 respectively Figures 17 and 18 show that our proposedscheme MobiL-AUV minimized the localization error andenhanced the network localization coverage up to 80 how-ever at the cost of energy consumption due to the localizationof each node In ACE-SingleRetransmission all the nodes inthe network take part in the cooperation process due towhichpacket delivery ratio increases at the cost of high energyconsumption Similarly in ACE-DoubleRetransmission tworelays participate in the cooperation process to achievenetwork throughput by compromising on energy

6 Conclusion

To minimize the localization and enhance the networkthroughput with efficient energy consumption two routingprotocols are proposed in this paper MobiL-AUV is pro-posed for the localization of the network In this schemethree mobile AUVs are deployed and equipped with GPSand act as reference nodes With the help of these referencenodes all the ordinary sensor nodes in the network arelocalized It achieved comparatively low localization errorand high network coverage because of less distance betweenmobile AUVs and nodes On the other hand CO-MobiLis presented to utilize the localization done by the MobiL-AUV In this scheme the network is divided into two regionsthat minimized the data load and reduced the energy con-sumption of sensor nodes deployed near the sink The use ofMRC as diversity technique enhanced the network through-put however at the cost of energy Extensive simulationresults showed that MobiL-AUV performs better in terms ofnetwork coverage and localization success ratio than MobiLand UDB whereas CO-MobiL outperformed its comparedexisting schemes (ACE-SingleRetransmission and ACE-DoubleRetransmission) in terms of throughput and energyconsumption


50 100 150 200Number of nodes

1 s time interval2 s time interval3 s time interval

0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio

(a) Node mobility = 1ms



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio

(b) Node mobility = 3ms


0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio


(c) Node mobility = 5ms

Figure 19 Normalized localization success ratio with respect to node mobility at various time intervals

Table 4 Performance trade-off

Protocol Achieved parameters Figure Compromised parameter Figure

CO-MobiL Network lifetime and throughput Figures 14 and 16 Energy consumption Figure 17

MobiL-AUV High localization coverage and lowlocalization error

Figure 18 Energy consumption Figure 17

ACE-SingleRetransmission Throughput Figure 16 Energy consumption Figure 17ACE-DoubleRetransmission Throughput Figure 16 Energy consumption Figure 17


Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This project was full financially supported by the King SaudUniversity through Vice Deanship of Research Chairs

References

[1] P Kirci and H Chaouchi ldquoRecursive and ad hoc routing basedlocalization in wireless sensor networksrdquo Computer Standardsand Interfaces vol 44 pp 258ndash263 2016

[2] T Ojha and S Misra ldquoMobiL a 3-dimensional localizationscheme for Mobile Underwater Sensor Networksrdquo in Proceed-ings of 2013National Conference on Communications NCC 2013ind February 2013

[3] H Maqsood N Javaid A Yahya B Ali Z A Khan and UQasim ldquoMobiL-AUV AUV-aided localization scheme forunderwater wireless sensor networksrdquo in Proceedings of 201610th International Conference on Innovative Mobile and InternetServices in Ubiquitous Computing (IMIS) pp 170ndash175 FukuokaJapan July 2016

[4] S Kundu and P Sadhukhan ldquoDesign and implementation of atime synchronization-free distributed localization scheme forunderwater acoustic sensor networkrdquo in Proceedings of 20152nd International Conference on Applications and Innovations inMobile Computing AIMoC 2015 pp 74ndash80 ind February 2015

[5] M Erol-Kantarci H T Mouftah and S Oktug ldquoA survey ofarchitectures and localization techniques for underwater acous-tic sensor networksrdquo IEEE Communications Surveys and Tuto-rials vol 13 no 3 pp 487ndash502 2011

[6] G Han A Qian X Li J Jiang and L Shu ldquoPerformanceevaluation of localization algorithms in large-scale UnderwaterSensor Networksrdquo in Proceedings of 2013 8th International ICSTConference on Communications and Networking in China CHI-NACOM 2013 pp 493ndash498 chn August 2013

[7] D Sivakumar and B Sivakumar ldquoLocalization using multilat-eration with RSS based random transmission directed localiza-tionrdquoMiddle-East Journal of Scientific Research vol 22 no 1 pp45ndash50 2014

[8] J XiongQQin andK Zeng ldquoAdistancemeasurementwirelesslocalization correction algorithm based onRSSIrdquo in Proceedingsof 7th International Symposium on Computational Intelligenceand Design ISCID 2014 pp 276ndash278 chn December 2014

[9] C Zhang Y Liu Z Guo G Sun and Y Wang ldquoMinimum costlocalization problem in three-dimensional ocean sensor net-worksrdquo in Proceedings of 2014 1st IEEE International Conferenceon Communications ICC 2014 pp 496ndash501 aus June 2014

[10] Z ZhuW Guan L Liu S Li S Kong and Y Yan ldquoAmulti-hoplocalization algorithm in underwater wireless sensor networksrdquoin Proceedings of the 6th International Conference on WirelessCommunications and Signal Processing (WCSPrsquo 14) pp 1ndash6Hefei China October 2014

[11] S Poursheikhali and H Zamiri-Jafarian ldquoTDOA based targetlocalization in inhomogenous underwater wireless sensor net-workrdquo in Proceedings of 5th International Conference on Com-puter and Knowledge Engineering ICCKE 2015 pp 1ndash6 irn

[12] Z Zhou Z Peng J-H Cui Z Shi and A Bagtzoglou ldquoScalablelocalization with mobility prediction for underwater sensor

networksrdquo IEEE Transactions on Mobile Computing vol 10 no3 pp 335ndash348 2011

[13] G Han C Zhang L Shu and J J P C Rodrigues ldquoImpacts ofdeployment strategies on localization performance in underwa-ter acoustic sensor networksrdquo IEEE Transactions on IndustrialElectronics vol 62 no 3 pp 1725ndash1733 2015

[14] P Carroll S Zhou KMahmood H Zhou X Xu and J-H CuildquoOn-demand asynchronous localization for underwater sensornetworksrdquo in Proceedings of OCEANS 2012MTSIEEEHamptonRoads Conference Harnessing the Power of the Ocean usaOctober 2012

[15] M T Isik and O B Akan ldquoA three dimensional localizationalgorithm for underwater acoustic sensor networksrdquo IEEETransactions on Wireless Communications vol 8 no 9 pp4457ndash4463 2009

[16] H Luo KWu Y Gong and L M Ni ldquoLocalization for driftingrestricted floating ocean sensor networksrdquo IEEETransactions onVehicular Technology vol 65 no 12 pp 9968ndash9981 2016

[17] F Mansourkiaie and M H Ahmed ldquoJoint cooperative routingand power allocation for collision minimization in wirelesssensor networks with multiple flowsrdquo IEEE Wireless Commu-nications Letters vol 4 no 1 2015

[18] W Fang F Liu F Yang L Shu and S Nishio ldquoEnergy-efficientcooperative communication for data transmission in wirelesssensor networksrdquo IEEE Transactions on Consumer Electronicsvol 56 no 4 pp 2185ndash2192 2010

[19] S S Ikki and M H Ahmed ldquoPerformance analysis of coop-erative diversity with incremental-best-relay technique overrayleigh fading channelsrdquo IEEE Transactions on Communica-tions vol 59 no 8 pp 2152ndash2161 2011

[20] Y Wei and D-S Kim ldquoExploiting cooperative relay for reliablecommunications in underwater acoustic sensor networksrdquo inProceedings of 33rd Annual IEEE Military CommunicationsConference MILCOM 2014 pp 518ndash524 usa October 2014

[21] F Mansourkiaie andM H Ahmed ldquoOptimal and near-optimalcooperative routing and power allocation for collision mini-mization inwireless sensor networksrdquo IEEE Sensors Journal vol16 no 5 pp 1398ndash1411 2016

[22] S Ahmed N Javaid F A Khan et al ldquoCo-UWSN Cooperativeenergy-efficient protocol for underwater WSNsrdquo InternationalJournal of Distributed Sensor Networks vol 2015 Article ID891410 2015

[23] Z Zhou S Zhou S Cui and J Cui ldquoEnergy-efficient cooper-ative communication in a clustered wireless sensor networkrdquoIEEE Transactions on Vehicular Technology vol 57 no 6 pp3618ndash3628 2008

[24] Y Li Z Jin X Wang and Z Liu ldquoRelay selection and opti-mization algorithm of power allocation based on channeldelay for UWSNrdquo International Journal of Future GenerationCommunication and Networking vol 9 no 2 pp 103ndash112 2016

[25] A Umar M Akbar Z Iqbal Z A Khan U Qasim and NJavaid ldquoCooperative partner nodes selection criteria for coop-erative routing in underwater WSNsrdquo in Proceedings of 5thNational Symposium on Information Technology Towards NewSmart World NSITNSW 2015 sau February 2015

[26] Z Liao D Li and J Chen ldquoA network access mechanism formultihop underwater acoustic local area networksrdquo IEEE Sen-sors Journal vol 16 no 10 pp 3914ndash3926 2016

[27] HWuMChen andXGuan ldquoAnetwork coding based routingprotocol for underwater sensor networksrdquo Sensors vol 12 no4 pp 4559ndash4577 2012


[28] A Wahid and D Kim ldquoAn energy efficient localization-freerouting protocol for underwater wireless sensor networksrdquoInternational Journal of Distributed Sensor Networks vol 2012Article ID 307246 11 pages 2012

[29] A Wahid S Lee and D Kim ldquoAn energy-efficient routing pro-tocol for UWSNs using physical distance and residual energyrdquoinProceedings of theOCEANS rsquo11 pp 1ndash6 Santander Spain June2011

[30] M Xu G Z Liu and H F Wu ldquoAn energy-efficient routingalgorithm for underwater wireless sensor networks inspiredby ultrasonic frogsrdquo International Journal of Distributed SensorNetworks vol 2014 Article ID 351520 12 pages 2014

[31] J Cao J Dou and S Dong ldquoBalance transmission mechanismin underwater acoustic sensor networksrdquo International Journalof Distributed Sensor Networks vol 2015 Article ID 429340 12pages 2015

[32] H Yang F Ren C Lin andB Liu ldquoEnergy efficient cooperationin underwater sensor networksrdquo in Proceedings of 2010 IEEE18th International Workshop on Quality of Service IWQoS 2010chn June 2010

[33] H Nasir N Javaid M Murtaza et al ldquoACE Adaptive cooper-ation in EEDBR for underwater wireless sensor networksrdquo inProceedings of 9th IEEE International Conference on Broadbandand Wireless Computing Communication and ApplicationsBWCCA 2014 pp 8ndash14 chn November 2014

[34] M Erol L F M Vieira and M Gerla ldquoAUV-aided localizationfor underwater sensor networksrdquo in Proceedings of Proceeding ofthe 2ndAnnual International Conference onWireless AlgorithmsSystems and Applications (WASA rsquo07) pp 44ndash54 Chicago IllUSA August 2007

[35] A K Othman A E Adams and C C Tsimenidis ldquoNodediscovery protocol and localization for distributed underwateracoustic networksrdquo in Proceedings of the Advanced InternationalConference on Telecommunications and International Confer-ence on Internet andWebApplications and Services GuadeloupeFrance February 2006

[36] S S Ikki and M H Ahmed ldquoPerformance analysis of incre-mental-relaying cooperative-diversity networks over Rayleighfading channelsrdquo IET Communications vol 5 no 3 pp 337ndash349 2011

[37] H Luo Y Zhao Z Guo S Liu P Chen and L M Ni ldquoUDBusing directional beacons for localization in underwater sensornetworksrdquo in Proceedings of 2008 14th IEEE InternationalConference on Parallel and Distributed Systems ICPADSrsquo08 pp551ndash558 aus December 2008

Submit your manuscripts athttpswwwhindawicom

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Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in




Anchor nodes

Nodes_Outside_Transmission_RangeA㰀

A㰀

A㰀

A㰀

A㰀

A㰀

A㰀

Figure 1 Anchor nodes coverage problem

the neighboring nodes to relay the data of a particular sourcenode to the destination The main techniques used to relaydata from the source node to the destination node are AF anddecode-and-forward (DF) In the AF relaying technique therelay node amplifies the received signal and then transmitsthe amplified version of the signal towards the destinationwhereas in the DF scheme the relay node decodes thereceived signal and then transmits the signal to the intendeddestination

After the localization the next objective is data routingFor this purpose various attempts in the literature have beenproposed In MobiL [2] anchor nodes deployed on watersurface are used as reference nodes for the localization ofordinary nodes However nodes that are not in the transmis-sion range of these anchor nodes are localized as shown inFigure 1 The nodes with label A1015840 are not in the transmissionrange of anchor nodes which results in higher chance ofthe localization error The anchor nodes do not provideenough coverage to localize the nodes So the remainingnonlocalized nodes will make reference to the other ordinarynodes resulting in a high localization error

To encounter these problems two localization routingschemes are proposed in this paper (i) MobiL-AUV [3] andCO-MobiL InMobiL-AUV three mobile AUVs are deployedunderwater at predefined depth (119889) The mobile AUVs accel-erate towards the surface to find their own three-dimensionalcoordinates via a GPS satellite and dive back to the under-water as shown in Figure 2 The mobile AUVs cover a largenetwork volume and act as reference nodes for nonlocalizednodes minimizing the localization error due to minimumdistance between mobile AUVs and nodes

We also present a region based cooperative routingmech-anism as shown in Figure 3 The nodes closer to the onshoresink (nodes in transmission range of sink) are considered inregion one and the rest of the nodes are considered in region2 Nodes in region 1 directly communicate with the sinkconsuming less energy On the other hand nodes in region2 communicate via a cooperatively chosen best relay


Mobile AUV

Figure 2 AUVs coverage area

Sink Base station

D

R

S

R1

R2

Figure 3 Region base cooperation

The remainder of the paper is organized as follows Therelated existing work is summarized in Section 2 Section 3discusses our scheme in a detail Then simulation resultsare presented and discussed in Section 4 and finally Sec-tion 5 concludes our work by discussing the findings of ourschemes

2 Related Work

In this section we discuss recent routing protocols forUWSNs in two categories (i) nodes mobility and localizationbased and (ii) cooperation based

21 Node Mobility and Localization In [4] the authorspropose a distributed localization technique for UWSNsTheauthors introduce two types of nodes anchor nodes andordinary nodesThe anchor nodes are used as reference nodeswhich are localized whereas the ordinary nodes do not knowtheir location The main focus is on the localization ofordinary nodes by using distributed localization techniques



























with less error




localization scheme







drawbacks






















efficiently














forecasting










anchor nodes




























3 Proposed Work







nodes




protocol










selection mechanism





topologies








communication










119910

119896(119889) 0) where V119909119896 and V

119910




V119909119896 (119889) =119899neigh

sum119898=1

119877119898119896V119909119898 (119889)

V119910119896 (119889) =

119899neigh

sum119898=1

119877119898119896V119910119898 (119889)

(1)


119899neigh119898=1 (1119903119898119896) represent





T1 T2 T3



AUV_1 AUV_2 AUV_3

KKKK K






119896(119889)) in (3) we


1199091198891015840 = 119909119889 + (1198792 minus 1198791) times V119909119896 (119889)

11990911988910158401015840 = 1199091198891015840 + (1198792 minus 1198791) times V119909119896 (119889)

1199101198891015840 = 119910119889 + (1198792 minus 1198791) times V119910119896 (119889)

11991011988910158401015840 = 1199101198891015840 + (1198792 minus 1198791) times V119910119896 (119889)

(3)



(1199091198891015840 minus 1199091198892)2+ (1199101198891015840 minus 1199101198892)

2+ (1199111198891015840 minus 1199111198892)

2= 11988922

(11990911988910158401015840 minus 1199091198893)2+ (11991011988910158401015840 minus 1199101198893)

2+ (11991111988910158401015840 minus 1199111198893)

2= 11988923

(4)

No

Yes


End




Start

deployment

Mobility prediction


message

beacon

If == 3beacon




D

D

S

S

Rb

Rb Best relay node

Destination node

Direct path

Source node

Through relay

Ysd=Hs

lowastg sd

+n sd

Ysr= Hs lowast

gsr+ nsr






119884119904119889 = 119867119904 times 119892119904119889 + 119899119904119889 (5)


119884119904119903 = 119867119904 times 119892119904119903 + 119899119904119903 (6)


119884119903119889 = 119884119904119903 times 119892119903119889 + 119899119903119889 (7)









(8)


119882weight =RE119889119894

(9)



Start


Mobility prediction

No

No

Yes

Yes

Node localization



Node is in region 2




End


threshold









D

S




120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)


120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)



D

D

S

S

Rb

Rb


Direct path

Source node

Relay

Sink


Data

Data

Data

ACKD

S

Rb






Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in





























with less error




localization scheme







drawbacks






















efficiently














forecasting










anchor nodes




























3 Proposed Work







nodes




protocol










selection mechanism





topologies








communication










119910

119896(119889) 0) where V119909119896 and V

119910




V119909119896 (119889) =119899neigh

sum119898=1

119877119898119896V119909119898 (119889)

V119910119896 (119889) =

119899neigh

sum119898=1

119877119898119896V119910119898 (119889)

(1)


119899neigh119898=1 (1119903119898119896) represent





T1 T2 T3



AUV_1 AUV_2 AUV_3

KKKK K






119896(119889)) in (3) we


1199091198891015840 = 119909119889 + (1198792 minus 1198791) times V119909119896 (119889)

11990911988910158401015840 = 1199091198891015840 + (1198792 minus 1198791) times V119909119896 (119889)

1199101198891015840 = 119910119889 + (1198792 minus 1198791) times V119910119896 (119889)

11991011988910158401015840 = 1199101198891015840 + (1198792 minus 1198791) times V119910119896 (119889)

(3)



(1199091198891015840 minus 1199091198892)2+ (1199101198891015840 minus 1199101198892)

2+ (1199111198891015840 minus 1199111198892)

2= 11988922

(11990911988910158401015840 minus 1199091198893)2+ (11991011988910158401015840 minus 1199101198893)

2+ (11991111988910158401015840 minus 1199111198893)

2= 11988923

(4)

No

Yes


End




Start

deployment

Mobility prediction


message

beacon

If == 3beacon




D

D

S

S

Rb

Rb Best relay node

Destination node

Direct path

Source node

Through relay

Ysd=Hs

lowastg sd

+n sd

Ysr= Hs lowast

gsr+ nsr






119884119904119889 = 119867119904 times 119892119904119889 + 119899119904119889 (5)


119884119904119903 = 119867119904 times 119892119904119903 + 119899119904119903 (6)


119884119903119889 = 119884119904119903 times 119892119903119889 + 119899119903119889 (7)









(8)


119882weight =RE119889119894

(9)



Start


Mobility prediction

No

No

Yes

Yes

Node localization



Node is in region 2




End


threshold









D

S




120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)


120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)



D

D

S

S

Rb

Rb


Direct path

Source node

Relay

Sink


Data

Data

Data

ACKD

S

Rb






Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in









with less error




localization scheme







drawbacks






















efficiently














forecasting










anchor nodes




























3 Proposed Work







nodes




protocol










selection mechanism





topologies








communication










119910

119896(119889) 0) where V119909119896 and V

119910




V119909119896 (119889) =119899neigh

sum119898=1

119877119898119896V119909119898 (119889)

V119910119896 (119889) =

119899neigh

sum119898=1

119877119898119896V119910119898 (119889)

(1)


119899neigh119898=1 (1119903119898119896) represent





T1 T2 T3



AUV_1 AUV_2 AUV_3

KKKK K






119896(119889)) in (3) we


1199091198891015840 = 119909119889 + (1198792 minus 1198791) times V119909119896 (119889)

11990911988910158401015840 = 1199091198891015840 + (1198792 minus 1198791) times V119909119896 (119889)

1199101198891015840 = 119910119889 + (1198792 minus 1198791) times V119910119896 (119889)

11991011988910158401015840 = 1199101198891015840 + (1198792 minus 1198791) times V119910119896 (119889)

(3)



(1199091198891015840 minus 1199091198892)2+ (1199101198891015840 minus 1199101198892)

2+ (1199111198891015840 minus 1199111198892)

2= 11988922

(11990911988910158401015840 minus 1199091198893)2+ (11991011988910158401015840 minus 1199101198893)

2+ (11991111988910158401015840 minus 1199111198893)

2= 11988923

(4)

No

Yes


End




Start

deployment

Mobility prediction


message

beacon

If == 3beacon




D

D

S

S

Rb

Rb Best relay node

Destination node

Direct path

Source node

Through relay

Ysd=Hs

lowastg sd

+n sd

Ysr= Hs lowast

gsr+ nsr






119884119904119889 = 119867119904 times 119892119904119889 + 119899119904119889 (5)


119884119904119903 = 119867119904 times 119892119904119903 + 119899119904119903 (6)


119884119903119889 = 119884119904119903 times 119892119903119889 + 119899119903119889 (7)









(8)


119882weight =RE119889119894

(9)



Start


Mobility prediction

No

No

Yes

Yes

Node localization



Node is in region 2




End


threshold









D

S




120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)


120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)



D

D

S

S

Rb

Rb


Direct path

Source node

Relay

Sink


Data

Data

Data

ACKD

S

Rb






Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in

















3 Proposed Work







nodes




protocol










selection mechanism





topologies








communication










119910

119896(119889) 0) where V119909119896 and V

119910




V119909119896 (119889) =119899neigh

sum119898=1

119877119898119896V119909119898 (119889)

V119910119896 (119889) =

119899neigh

sum119898=1

119877119898119896V119910119898 (119889)

(1)


119899neigh119898=1 (1119903119898119896) represent





T1 T2 T3



AUV_1 AUV_2 AUV_3

KKKK K






119896(119889)) in (3) we


1199091198891015840 = 119909119889 + (1198792 minus 1198791) times V119909119896 (119889)

11990911988910158401015840 = 1199091198891015840 + (1198792 minus 1198791) times V119909119896 (119889)

1199101198891015840 = 119910119889 + (1198792 minus 1198791) times V119910119896 (119889)

11991011988910158401015840 = 1199101198891015840 + (1198792 minus 1198791) times V119910119896 (119889)

(3)



(1199091198891015840 minus 1199091198892)2+ (1199101198891015840 minus 1199101198892)

2+ (1199111198891015840 minus 1199111198892)

2= 11988922

(11990911988910158401015840 minus 1199091198893)2+ (11991011988910158401015840 minus 1199101198893)

2+ (11991111988910158401015840 minus 1199111198893)

2= 11988923

(4)

No

Yes


End




Start

deployment

Mobility prediction


message

beacon

If == 3beacon




D

D

S

S

Rb

Rb Best relay node

Destination node

Direct path

Source node

Through relay

Ysd=Hs

lowastg sd

+n sd

Ysr= Hs lowast

gsr+ nsr






119884119904119889 = 119867119904 times 119892119904119889 + 119899119904119889 (5)


119884119904119903 = 119867119904 times 119892119904119903 + 119899119904119903 (6)


119884119903119889 = 119884119904119903 times 119892119903119889 + 119899119903119889 (7)









(8)


119882weight =RE119889119894

(9)



Start


Mobility prediction

No

No

Yes

Yes

Node localization



Node is in region 2




End


threshold









D

S




120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)


120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)



D

D

S

S

Rb

Rb


Direct path

Source node

Relay

Sink


Data

Data

Data

ACKD

S

Rb






Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in







nodes




protocol










selection mechanism





topologies








communication










119910

119896(119889) 0) where V119909119896 and V

119910




V119909119896 (119889) =119899neigh

sum119898=1

119877119898119896V119909119898 (119889)

V119910119896 (119889) =

119899neigh

sum119898=1

119877119898119896V119910119898 (119889)

(1)


119899neigh119898=1 (1119903119898119896) represent





T1 T2 T3



AUV_1 AUV_2 AUV_3

KKKK K






119896(119889)) in (3) we


1199091198891015840 = 119909119889 + (1198792 minus 1198791) times V119909119896 (119889)

11990911988910158401015840 = 1199091198891015840 + (1198792 minus 1198791) times V119909119896 (119889)

1199101198891015840 = 119910119889 + (1198792 minus 1198791) times V119910119896 (119889)

11991011988910158401015840 = 1199101198891015840 + (1198792 minus 1198791) times V119910119896 (119889)

(3)



(1199091198891015840 minus 1199091198892)2+ (1199101198891015840 minus 1199101198892)

2+ (1199111198891015840 minus 1199111198892)

2= 11988922

(11990911988910158401015840 minus 1199091198893)2+ (11991011988910158401015840 minus 1199101198893)

2+ (11991111988910158401015840 minus 1199111198893)

2= 11988923

(4)

No

Yes


End




Start

deployment

Mobility prediction


message

beacon

If == 3beacon




D

D

S

S

Rb

Rb Best relay node

Destination node

Direct path

Source node

Through relay

Ysd=Hs

lowastg sd

+n sd

Ysr= Hs lowast

gsr+ nsr






119884119904119889 = 119867119904 times 119892119904119889 + 119899119904119889 (5)


119884119904119903 = 119867119904 times 119892119904119903 + 119899119904119903 (6)


119884119903119889 = 119884119904119903 times 119892119903119889 + 119899119903119889 (7)









(8)


119882weight =RE119889119894

(9)



Start


Mobility prediction

No

No

Yes

Yes

Node localization



Node is in region 2




End


threshold









D

S




120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)


120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)



D

D

S

S

Rb

Rb


Direct path

Source node

Relay

Sink


Data

Data

Data

ACKD

S

Rb






Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in




T1 T2 T3



AUV_1 AUV_2 AUV_3

KKKK K






119896(119889)) in (3) we


1199091198891015840 = 119909119889 + (1198792 minus 1198791) times V119909119896 (119889)

11990911988910158401015840 = 1199091198891015840 + (1198792 minus 1198791) times V119909119896 (119889)

1199101198891015840 = 119910119889 + (1198792 minus 1198791) times V119910119896 (119889)

11991011988910158401015840 = 1199101198891015840 + (1198792 minus 1198791) times V119910119896 (119889)

(3)



(1199091198891015840 minus 1199091198892)2+ (1199101198891015840 minus 1199101198892)

2+ (1199111198891015840 minus 1199111198892)

2= 11988922

(11990911988910158401015840 minus 1199091198893)2+ (11991011988910158401015840 minus 1199101198893)

2+ (11991111988910158401015840 minus 1199111198893)

2= 11988923

(4)

No

Yes


End




Start

deployment

Mobility prediction


message

beacon

If == 3beacon




D

D

S

S

Rb

Rb Best relay node

Destination node

Direct path

Source node

Through relay

Ysd=Hs

lowastg sd

+n sd

Ysr= Hs lowast

gsr+ nsr






119884119904119889 = 119867119904 times 119892119904119889 + 119899119904119889 (5)


119884119904119903 = 119867119904 times 119892119904119903 + 119899119904119903 (6)


119884119903119889 = 119884119904119903 times 119892119903119889 + 119899119903119889 (7)









(8)


119882weight =RE119889119894

(9)



Start


Mobility prediction

No

No

Yes

Yes

Node localization



Node is in region 2




End


threshold









D

S




120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)


120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)



D

D

S

S

Rb

Rb


Direct path

Source node

Relay

Sink


Data

Data

Data

ACKD

S

Rb






Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in




D

D

S

S

Rb

Rb Best relay node

Destination node

Direct path

Source node

Through relay

Ysd=Hs

lowastg sd

+n sd

Ysr= Hs lowast

gsr+ nsr






119884119904119889 = 119867119904 times 119892119904119889 + 119899119904119889 (5)


119884119904119903 = 119867119904 times 119892119904119903 + 119899119904119903 (6)


119884119903119889 = 119884119904119903 times 119892119903119889 + 119899119903119889 (7)









(8)


119882weight =RE119889119894

(9)



Start


Mobility prediction

No

No

Yes

Yes

Node localization



Node is in region 2




End


threshold









D

S




120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)


120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)



D

D

S

S

Rb

Rb


Direct path

Source node

Relay

Sink


Data

Data

Data

ACKD

S

Rb






Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in




Start


Mobility prediction

No

No

Yes

Yes

Node localization



Node is in region 2




End


threshold









D

S




120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)


120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)



D

D

S

S

Rb

Rb


Direct path

Source node

Relay

Sink


Data

Data

Data

ACKD

S

Rb






Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in








D

S




120574119860119865 = 120574119904119903119889 + 120574119904119889 (10)


120574119904119903119889 =120574119904119903120574119903119889120574119904119903 + 120574119903119889 + 1

(11)



D

D

S

S

Rb

Rb


Direct path

Source node

Relay

Sink


Data

Data

Data

ACKD

S

Rb






Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in




Data

Data

Data

D

S

Rb

NACK













60

80

100

120

140

160

180

200

Aliv

e nod

es

500 1000 1500 20000Round








0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in




0 200 400 600 800 1000 1200 1400 1600 1800Round

0

20

40

60

80

100

120

140

160

180

200

Num

ber o

f rec

eive

d pa

cket

s







0

5

10

15

Ener

gy co

nsum

ptio

n

200 400 600 800 1000 1200 1400 1600 18000Round

CO-MobiL


Error threshold

0

05

1

15

2

25

3

35

4

45

5Lo

caliz

atio

n er

ror (

m)


CO-MobiL





MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in




MobiLMobiL-AUV

50 100 150 200

Number of nodes

0

10

20

30

40

50

60

70

80

90

100

Loca

lizat

ion

cove

rage

()

UDB








6 Conclusion





0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in






0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio




0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio



0

01

02

03

04

05

06

07

08

09

1

Nor

mal

ized

succ

ess r

atio













Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in






Acknowledgments


References















































Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in





















Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in










Advances in

FuzzySystems


Volume 2014












Journal of



Advances in

Multimedia


Biomedical Imaging


Advances in


RoboticsJournal of










Advances in



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A Localization Based Cooperative Routing Protocol for ...downloads.hindawi.com/journals/misy/2017/7954175.pdf · ResearchArticle A Localization Based Cooperative Routing Protocol