Imane BENKHELIFA Research Associate , CERIST, Algeria 1 st year PhD Student , USTHB, Algeria

GEOGRAPHIC ROUTING PROTOCOLS IN WIRELESS

SENSOR NETWORKS FOCUS ON REAL TIME ROUTING AND PROTOCOLS SUPPORTING MOBILITY

Imane BENKHELIFA

Research Associate, CERIST, Algeria

1st year PhD Student, USTHB, Algeria

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OUTLINE

Routing Protocols

Cliassification of Routing Protocols

Geographic Protocols

QoS Routing Protocols

MultiPath Protocols

Routing Protocols supporting Mobility

Routing Protocols with Localization Errors

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ROUTING PROTOCOL

Design Constraints for routing in WSN: Autonomy: nodes make decisions

Energy Efficiency: Prolonging network life time while maintaining a good grade of connectivity

Scalability: works with a large amount of nodes

Resilience: if some nodes stop operating, an alternative route should be discovered

Device heterogeneity: the use of nodes with different processors, transceivers, power units or sensing components

Mobility Adaptability: supports the mobility of nodes (sinks, events…)

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ROUTING PROTOCOL

Additional constraints for certain applications such as “Emergency Response”:

Stateless Architecture: it does not require routing table minimum memory

Soft Real-time: minimum delay

QoS Routing and Congestion Management : avoids congestion, re-routes packets, minimum control overhead

Traffic Load Balance: multi path, concurrent routes

Localized behavior: only delay changes will be sent to neighbors

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OUTLINE

Routing Protocols




MultiPath Protocols



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CLASSIFICATIONRouting

Network Structure

Flat

DD,SPIN,RR,MCFA

Hierarchic

TEEN,LEACH,TTDD

Geographic

SPEED,GOAFR,GEER

Protocol operations

Negociation

SPIN

Query

DD,Rumor

QoS

SAR,SPEED,MMSPEED

Multi-Path

Braided, N to 1

Coherence

Rumor

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OUTLINE

Routing Protocols




MultiPath Protocols



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GEOGRAPHIC ROUTING IN WSN

Motivations of Using Geographic Routing Approach in WSNs

Simplicity: simple calculations

Stateless: memory conservation

Autonomy: nodes make decisions

Energy Efficiency: prolonging network life time while maintaining a good grade of connectivity

Scalability: works with a large amount of nodes

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Forwarding techniques in geographic routing are: Compass routing(C), GRS(G), MFR(M) and NFP(N)

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Greedy Algorithms: choosing among neighbors the nearest to the sink (the Euclidian distance is a metric of choosing), the process repeats until the packet reaches the final destination,

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Drawback: if the current holder has no neighbors closer to the destination than itself !!!!!

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GEOGRAPHIC ROUTING IN WSN GAF (Geographic Adaptive Fidelity):

Forms a virtual grid of the covered area Three node states: Discovery, Active and Sleep Each node associates itself with a cell in the grid based on its

location Nodes associated with the same cell are equivalent Some nodes in an area are kept sleeping to conserve energy Nodes change state from sleeping to active for load balancing

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GAF Advantages: Increase the lifetime of the network significantly Considered to be hierarchical protocol

Each sub-region is a cluster Representative node is a cluster head

GAF Disadvantages: Does not perform any data aggregation Not very scalable Overhead of forming the grid Only the active nodes sense and report data data

accuracy is not very high

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OUTLINE

Routing Protocols




MultiPath Protocols



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QOS ROUTING PROTOCOLS IN WSN

Motivations of Using QoS Routing Approach in WSNs

Ensure Quality of Service in terms of :

Delay Bandwith Energy Load Balancing

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SPEED:

Aims to reduce the End-to-End deadline miss ratio

Supposes that E2E Deadlines are proportional to the distance between the source and the destination using feed-back control

Guarantees deadline by maintaining a packet delivery speed across the network.

Velocity = Distance (s,d) / required deadline

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SPEED:

The forwarding nodes are calculated from the neighbor nodes having to be at least k distance closer to the destination

If no speed matches, a neighborhood feed-back determines whether to drop the packet or to re-route it

S F DR

K

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OUTLINE

Routing Protocols




MultiPath Protocols



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MULTIPATH GEOGRAPHIC ROUTING IN WSN

Motivations of Using Multipath Routing Approach in WSNs

Reliability and Fault-Tolerance

Load Balancing and Bandwidth Aggregation

QoS Improvement

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MMSPEED (Multi path Multi SPEED): Introduces multiple speed levels (layers) to guarantee

timeliness packet delivery Each packet is assigned to a speed layer and then

placed in a queue High priority before low priority Source determines for each packet the speed regarding

the destination and its specific E2E deadline If an intermediate node perceives that this packet

cannot meet its specific deadline, the intermediate selects another speed layer

Reliability is guaranteed by controlling active paths and sending multiple copies

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MMSPEED (Multi path Multi SPEED):

A

B

C

D = distance A-C – distance B-C

distance

A-B

distance B-C destination

Geographic progress that can be made towards the destination by selecting node B as the next forwarder

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Challenges:

The main disadvantage lies in the cost of maintaining the paths.

This cost comprises in memory resources and network overhead so not suitable for networks critically by their reduced batteries.

However, they become necessary when reliability is a strong requirement

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OUTLINE

Routing Protocols




MultiPath Protocols



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ROUTING PROTOCOLS SUPPORTING MOBILITY IN WSN

Motivations of Using Routing Approach in WSNs with mobile sinks

Mobile sinks prolong the networks lifetime

Load Balancing and Bandwidth Aggregation

QoS Improvement

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TTDD (Two Tier Data Dissemination): Static sensors vs Mobile sinks Each active source creates a grid over the static

network with grid points acting as dissemination nodes. A mobile sink sends out a locally controlled flood that

discovers its nearest dissemination point.

D

S

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ALURP (Adaptive Local Update-based Routing Protocol): The adaptive area is constructed as the circle (VC, Dvc,sink).

DN

VC

Area B

Area A

DNA

DNB

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Problem: When the sink moves

toward the VC, the DN still keep the previous location of the sink and therefore will send the packet to a wrong place, because sink informs only the new area about its new location.

Solution:• Inform the former adaptive area but not the current

adaptive area to flush the topology information of the sink.

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ALURP Advantages:

Saves energy and keeps communication with sensors and sink thanks to the adaptive area.

The destination area can be expressed by its radius R.

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ALURP Drawbacks:

How to inform only the former adaptive area but not the current adaptive area ?????

DN may excessively consume energy, because source always sends data to the DN instead of the sink, which can be a bottleneck !!!!!!

If the destination area is too small and sink changes frequently its position too much of energy consumption by sensors to update routes !!!!!

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Energy-Efficient Routing in MWSN using Mobility Prediction: Mobile sink estimates and tracks its state (location,

velocity, acceleration) from noisy measurements with a kalman filter.

The source predicts the location of the mobile sink

The state of the predictor is updated by receiving STATE-UPDATE from the mobile sink.

The STATE-UPDATE is only sent when the Euclidean norm of the error between the predicted state and the estimated state by Kalman Filter exceeds a pre-defined threshold.

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The STATE-UPDATE and DATA messages are forwarded in a multi hop fashion

Uses greedy forwarding.

ELASTIC:

A

-A node uses greedy forwarding-The mobile sink broadcasts its new position every 1 m -Each node listens to the transmission of his successor and detects the change of the sink position and changes it for its next transmission- The process repeats until the source node

B


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OUTLINE

Routing Protocols




MultiPath Protocols



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ROUTING PROTOCOLS WITH LOCALIZATION ERRORS

Motivations of Using Routing protocols with Localization Errors

Nodes’ positions are not always accurate

If the packet contains a wrong position , the packet will not reach its destination

QoS Improvement by introducing localization errors in routing decisions

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ELLIPSE The region is defined by an ellipse source position, sink

position, distance between them, an ellipse factor “ l ”. All nodes in the ellipse region and those who receive

msg, forward it with a probability “ p ”. Neighbors of source and sink always forward msg even if

they are out of the ellipse.

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ELLIPSEAssumptions:

probability “p ” defines a sub-set of nodes which will relay msg towards destination

before deployment, all the sensors know the ellipse factor and destination position

before sending , the source includes its position (xs, ys)

when sensor “u” receives a msg, it checks whether it is inside the ellipse by the following formula:

Dsu + Dud <= l.d where l: ellipse factor, d: distance between source and sink

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Localization error management in ELLIPSE:

When the source is not accurately located, because it’s an important parameter to define the ellipse: all neighbors of the source have to forward msg (to relay nodes) even if they are outside the ellipse.

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Localization error management in ELLIPSE:

Problem: to how many hops?? If h=1 all 1-hop neighbors are relay nodes

Solution: the minimal number of hops to reach sensors close to S is the ceiling of [/r]. To avoid dropping msg: h>= [/r] +1

Problem: when the node’s position is not accurate, because it cannot determine if it is inside the ellipse it cannot determine if it is a relay node.

Solution: each potential relay node can calculate its probability to be inside the ellipse PA= AA / ²A….where AA is the intersection of the circle of A and the ellipse

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Summary: Managing Localization error leads to significant energy

consumption Suitable to mobile network because there’s no need to

know neighbors position

Drawbacks: Does not focus on the broadcasting strategy inside the

ellipse !!! Why choosing Ellipse as a region and not other region

form???

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SUMMARY

Protocol Category

Greedy Forwarding Geographic

GAF Geographic

SPEED QoS-based

MMSPEED MultiPath-based & QoS-based

TTDD, ALURP, EERMP, ELASTIC Geographic supporting Mobility

ELLIPSE Geographic with localization error

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Imane BENKHELIFA Research Associate , CERIST, Algeria 1 st year PhD Student , USTHB, Algeria