grammati pantziou 1, aristides mpitziopoulos 2, damianos gavalas 2, charalampos konstantopoulos 3,...
TRANSCRIPT
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
MobiCluster protocol
Rendezvous sensor node
Cluster Head
Sensor node
Phase 1: Clustering
MobiCluster protocol
Sensor node
Cluster Head
Phase 1: Clustering
MobiCluster protocol
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
Rendezvous sensor node
Cluster Head
Sensor node
Phase 3: CHs attachment to RNs◦ RN_Attach (CH = 1; hops = 1)
MobiCluster protocol
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
MobiCluster protocol
Phase 4: Data aggregation and forwarding to the RNs
MobiCluster protocol
Phase 5: Communication between RNs and mobile sinks
MobiCluster protocol
POLL transmission range
Rendezvous sensor node
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
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