grammati pantziou 1, aristides mpitziopoulos 2, damianos gavalas 2, charalampos konstantopoulos 3,...

A Rendezvous-Based Approach Enabling Energy-Efficient Sensory Data Collection with Mobile Sinks

Grammati Pantziou1, Aristides Mpitziopoulos2, Damianos Gavalas2,

Charalampos Konstantopoulos3, and Basilis Mamalis1

1 Department of Informatics, Technological Educational Institution of Athens, Athens, Greece2 Department of Cultural Informatics, University of the Aegean Mytilene, Lesvos, Greece

3 Department of Informatics, University of Piraeus Piraeus, Greece

IEEE Transactions On Parallel And Distributed Systems (TPDS) 2011

Introduction Related work Goals Assumptions MobiCluster protocol Simulation Conclusions

Outline

A main reason of energy spending in WSNs relates with communicating the sensor readings from the sensor nodes (SNs) to remote sinks.◦ These readings are typically relayed using ad hoc multi-hop routes in

the WSN Energy is consumed faster A non-uniform depletion of energy

◦ A mobile sink (MS) moving through the network deployment region can collect data from the static SNs Reduces the energy consumption Prolonging the network lifetime

Introduction

A large class of monitoring applications involve a set of urban areas (e.g. urban parks or building blocks) ◦ surveillance ◦ fire detection

In these environments, individual monitored areas are typically covered by isolated ‘sensor islands’◦ mobile nodes cannot move through but only approach the periphery of

the network deployment region

Introduction

The movement of mobile robots is controllable◦ impractical in realistic urban traffic conditions

No strategy is used to appoint suitable nodes as RNs

Related work

Rendezvous sensor node

◦ Knowledge of network topology◦ The whole algorithm is performed centrally

Related work

A common characteristic of all techniques described◦ they do not take into account the contact time of a RN with the MS

during which it can send the buffered data

◦ there is no special focus on the amount of data the RNs receive from the other nodes of the network

◦ this considerably reduces the actual data delivery rate to the MS

Related work

This paper proposed protocol called MobiCluster◦ minimizing the overall network overhead◦ balanced energy consumption◦ prolonged network lifetime

Goals

MSs are mounted upon public buses◦ fixed trajectories◦ near-periodic schedule

Sensors are deployed in urban areas in proximity to public transportation vehicle routes.

SNs are location-unaware

Assumptions

Phase 1: Clustering Phase 2: RNs selection Phase 3: CHs attachment to RNs Phase 4: Data aggregation and forwarding to the RNs Phase 5: Communication between RNs and mobile sinks

MobiCluster protocol

Overview



Cluster Head

Sensor node

Phase 1: Clustering


Sensor node

Cluster Head

Phase 2: RNs selection

MobiCluster protocol_ _ ( . _ , . , . , . )val first lastRN Cand Msg v Node ID v Comp v T v T

11 2 3

max

.bn

iresidual ival b

b

sEv Comp n

E n

pre-specified thresholdresidualE

RN => CH

CH

1 2 | |

RN

, , ... , ( . . . , , 1 | | )u

u

uj val i valR

v R

v v v v Comp v Comp i j i j R


Cluster Head

Sensor node

Phase 3: CHs attachment to RNs◦ RN_Attach (CH = 1; hops = 1)


21

3 4CH #4

RN_Attach (CH = 1; hops = 2)

RN_Attach (CH = 2; hops = 1)

Phase 4: Data aggregation and forwarding to the RNs


Phase 5: Communication between RNs and mobile sinks


POLL transmission range


Cluster Head

Sensor node

POLL

Sensor node 200,400,600,800,1000

Aggregation ratiof1=60%, f2=5%f1, f2=0%f1, f2=100%

Simulation

Simulation

Increased data throughput is ensured by regulating the number of RNs for allowing sufficient time to deliver their buffered data and preventing data losses.

Enables balanced energy consumption

Conclusions

grammati pantziou 1, aristides mpitziopoulos 2, damianos gavalas 2, charalampos konstantopoulos 3,...

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