1. Grammati Pantziou 1, Aristides Mpitziopoulos 2, Damianos Gavalas 2, Charalampos Konstantopoulos 3, and Basilis Mamalis 1 1 Department of Informatics, Technological Educational Institution of Athens, Athens, Greece 2 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

2.  Introduction  Related work  Goals  Assumptions  MobiCluster protocol  Simulation  Conclusions

3.  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

4.  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

5.  The movement of mobile robots is controllable ◦ impractical in realistic urban traffic conditions  No strategy is used to appoint suitable nodes as RNs Rendezvous sensor node

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

7.  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

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

9.  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

10.  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

11.  Overview Rendezvous sensor node Cluster Head Sensor node

12.  Phase 1: Clustering BEACON transmission range Sensor node Cluster Head

13.  Phase 1: Clustering Sensor node Cluster Head BEACON transmission range

14.  Phase 2: RNs selection RN => CH CH Rendezvous sensor node Cluster Head Sensor node

15.  Phase 3: CHs attachment to RNs ◦ RN_Attach (CH = 1; hops = 1) 2 1 3 4 CH #4 RN_Attach (CH = 1; hops = 2) RN_Attach (CH = 2; hops = 1)

16.  Phase 4: Data aggregation and forwarding to the RNs

18.  Phase 5: Communication between RNs and mobile sinks POLL transmission range Rendezvous sensor node Cluster Head Sensor node POLL

19. Sensor node200,400,600,800,1000 Aggregation ratio f 1 =60%, f 2 =5% f 1, f 2 =0% f 1, f 2 =100%

23.  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