A Survey on Routing Protocols for Wireless Sensor

Networks

Kemal Akkaya, Mohamed Younis19th July, 2005Seo, DongMahn

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Contents Introduction Data-centric protocols Hierarchical protocols Location-based protocols Network flow and QoS-aware protocols Conclusion and Open Issues

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Introduction (1) Micro Sensor

micro-electro-mechanical systems (MEMS) , low power and highly integrated digital electronics

data processing, communication capabilitiesambient conditionsan electric signalcommand center (sink)data concentration center (gateway)disposable, unattendedmilitary, civil application, dangerous mission,

landmineconstraints – energy supply, bandwidth

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Introduction (2) Routing in sensor networks

Characteristics No global addressing scheme require the flow of sensed data from multiple regions (sources) to a

particular sink redundancy of data traffic constraints - transmission power, on-board energy, processing capac

ity and storage classification

data-centric hierarchical location-based network flow QoS awareness

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Introduction (3)

System Architecture and Design IssuesNetwork DynamicsNode DeploymentEnergy ConsiderationsData Delivery ModelsNode CapabilitiesData Aggregation/Fusion

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Introduction (4) Related Work

I.F. Akyildiz et al., “Wireless sensor networks: a survey”, Computer Networks, Vol. 38, pp. 393-422, March 2002.

survey of design issues and techniques physical constraints protocols proposed in all layers of network stack No classification of routing protocol

S.Tilak et al., “A Taxonomy of Wireless Microsensor Network Models”, in ACM Mobile Computing and Communication Review (MC2R), June 2002.

high level description of typical sensor network architecture classification of sensor network with considering several architectur

al factors No routing protocol

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Data-centric protocols (1)

Flooding and Gossiping

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Data-centric protocols (2)

Sensor Protocols for Information via Negotiation (SPIN)

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Data-centric protocols (3)

Directed Diffusion

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Data-centric protocols (4) Energy-aware routing

set of sub-optimal pathmeans of a probability function, energy

consumption of each pathnetwork survivability3 phases

Setup phase localized flooding - to find routes and to create the

routing tables)Data Communication Phase

randomly choosing a nodeRoute maintenance phase

localized flooding - to keep all the paths alive

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Data-centric protocols (5)

Rumor routingvariation of DDbetween event flooding and query floodingagent (event flooding), query floodingevent tableSimulation result

significant evergy savingcan handle node’s failureonly when the number of events is small

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Data-centric protocols (6) Gradient-Based Routing (GBR)

changed version of DDheight of the node – number of hopsgradient – difference between a node’s

height and that of is neighborthe largest gradientdata combining entity (to aggregate data)three different data spreading techniques

Stochastic SchemeEnergy-based schemeStream-based scheme

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Data-centric protocols (7) Constrained anisotropic diffusion routing

(CADR) information-driven sensor querying (IDSQ)constrained anisotropic diffusion routing (CADR)maximizing the information gainminimizing the latency and bandwidthCADR

evaluation of information/cost/cost objective and routes

based on local information/cost gradient and end-user requirements

IDSQquery node - the most useful information

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Data-centric protocols (8) COUGAR

a huge distributed database system

select a leader nodenetwork-layer

independent solutiondrawbacks

extra overheadsynchronizationfailure of leader nodes

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Data-centric protocols (9) Active Query forwarding In sensoR nEtworks (A

CQUIRE)new data-centric mechanisma distributed database, complex queriesone-shot respond partially and forward to another sensor look-ahead of d hopsd = 4, mathematical modelingno validation of result through simulation

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Hierarchical protocols (1)

Low-Energy Adaptive Clustering Hierarchy (LEACH)clusters of the sensor nodes5% of the total number of all sensor nodeschoosing header with random number

between 0 and 1not for large networkdynamic clustering with extra overhead

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Hierarchical protocols (2)

PEGASIS & Hierarchical-PEGASISPower-Efficient Gathering in Sensor

Information Systemschains from sensor nodes

Hierarchical-PEGASISchain based binary schemeCDMA, spatially separated nodes

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Hierarchical protocols (3) TEEN and APTEEN

Threshold sensitive Energy Efficient sensor Network Protocol

clustering, hard and soft thresholds, TDMAnot good for periodic applications

AdaPtive Threshold sensitive Energy Efficient sensor Network protocol

hybrid network, TDMA (intra), CDMA (inter)periodic data collections and reacting to time-critical eve

ntsthree query types

historical, to analyze past data values one-tome, to take a snapshot view of the network persistent to monitor an event for a period of time

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Hierarchical protocols (4)

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Hierarchical protocols (5)

Energy-aware routing for cluster-based sensor networks 3 tier architecture

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Hierarchical protocols (6)

Self-organizing protocolbased on taxonomyRouter nodeLocal Markov Loops (LML)4 phases

Discovery phaseOrganization phaseMaintenance phaseSelf-reorganization phase

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Location-based protocols (1) MECN & SMECN

Minimum Energy Communication Networkminimum energy network for wireless networksutilizing low power GPS2 phases

two-dimensional plane,sparse graph (enclosure)

find optimal links with distributed Belmann-Ford shortest pathalgorithm

Small MECNcan transmit to every

other node

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Location-based protocols (2)

Geographic Adaptive Fidelity (GAF)energy-aware location-based routing

algorithmad hoc networks, GPS

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Location-based protocols (3)

Geographic and Energy Aware Routing (GEAR)use of geographic information to restrict the number of interests in DD2 phases

Forwarding packet towards the target region

Forwarding the pachkts within the region

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Network flow and QoS-awareprotocols (1) Maximum lifetime energy routing

network flow approachmaximize network lifetimeMinimum Transmitted Energy (MTE)

algorithmBellman-Ford shortest path algorithm

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Network flow and QoS-awareprotocols (2) Maximum lifetime data gathering

Maximum Lifetime Data Aggregation (MLDA)

Lifetime Tdata-gathering schedule SMaximum Lifetime Data Routing (MLDR)

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Network flow and QoS-awareprotocols (3) Minimum cost forwarding

minimum cost patheffect of delay, throughput and energy

consumption from any node to the sink2 phases

setup phasesecond phase

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Network flow and QoS-awareprotocols (4) Sequential Assignment Routing (SAR)

the first protocol table-driven multi-path approach taking QoS metric, energy resource on each path a

nd priority level of each packet fault-tolerance and easy recoveryoverhead of maintaining the tables and states at e

ach sensor node

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Network flow and QoS-awareprotocols (5) Energy-Aware QoS Routing Protocol

extended versionof Dijkstra’salgorithm

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Network flow and QoS-awareprotocols (6) SPEED

soft real-time end-to-end guaranteesend-to-end delay for the packetscongestion avoidancerouting module – Stateless Geographic Non-

Deterministic forwarding (SNFG)

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Conclusion and Open Issues (1)

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Conclusion and Open Issues (2)

more issuesQuality of Service (QoS)

video and imaging sensorsreal-time applications

Energy-aware QoS routingnode mobility integration of WSN with wired networks

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