TELKOM/NOKIA SIEMENS NETWORKS/ TELESCIENCES/UCT-US COE SEMINAR

1. TELKOM/NOKIA SIEMENS NETWORKS/TELESCIENCES/UCT-US COE SEMINAR Clustering Algorithm to Improve Energy Efficiency for Homogeneous Sensor Networks Dali Wei Supervisor: H Anthony Chan

2. Outline • Introduction • What is an ad hoc network • Where is it in NGN • Sensor networks and Mobile Ad Hoc Networks (MANET) • Topology: flat and hierarchical clustering • PhD thesis and presentation content • Existing energy-efficient clustering algorithms for sensor networks • Proposed clustering algorithm • Simulation • Conclusion

3. What is an ad hoc network • Ad Hoc Networks • multi-hop systems • each node can act as a router • pre-set infrastructure is unnecessary

4. Where is it in NGN Fixed Wireless (IEEE) Wireless (Cellular) Service Layer Next Generation Network Control Layer Transport Layer xDSL, FTTX, Cable, PSTN, etc. WiMAX 802.16, 802.21 WLAN 802.11b/a/g/n Bluetooth 802.15 Ad Hoc 802.15.4 GSM,EDGE,UMTS,HSDPA,HSUPA (3GPP) Cdma2000 (3GPP2) 4G Ad Hoc (IETF)

5. Sensor networks and Mobile Ad Hoc Networks • A Sensor network • It usually has a sink • Nodes are usually stationary • Data traffic is towards the sink • A Mobile Ad Hoc Network • It has not a sink • Nodes are usually moveable

6. Topology (a) Flat topology (b) Hierarchical clustering topology

7. PhD Thesis and Presentation Content • PhD Thesis Clustering Algorithms for Sensor Networks and MANETs to Improve Energy Efficiency Major Contribution: (1) Balancing power consumption throughout the network (2) Saving energy Sensor Networks with High Node Density Sensor Networks with Low to Medium Node Density MANETs

8. Outline • Introduction • Existing energy-efficient clustering algorithms for sensor networks • Classification of clustering algorithms • Analysis of existing algorithms • Directional data traffic towards the sink • Power consumption of locating CH at different places • Proposed clustering algorithm • Simulation • Conclusion

9. Classification of Clustering Algorithms • Aggregating data • Distributing the higher burden of CH among nodes • Equalizing cluster size • Reducing power consumption of intra-cluster communication • Assigning the lowest need power to each link

10. Analysis of Existing Algorithms • 1. Directional data traffic towards the sink: • In a single-hop system, the cluster farther away from the sink dies earlier as it needs higher power to reach the sink • In a multi-hop system, the cluster nearer the sink dies earlier as it needs to relay more data from others CH2 CH6 CH4 CH1 CH3 CH5 Data Sink

11. Analysis of Existing Algorithms 5 19 11 16 14 2 6 8 12 18 10 13 3 7 4 17 9 20 15 1 • 2. Power consumption of locating CH at different places CH

12. Outline • Introduction • Existing energy-efficient clustering algorithms for sensor networks • Proposed clustering algorithm • Strategy • Proposed clustering algorithm: • Cluster organization and data communication • Equalizing cluster lifetime • Maintaining CH at the centre area of the cluster • Simulation • Conclusion

13. Strategy • 1. Equalizing cluster lifetime • 2. Distributed, but centralized to initiate the cluster formation

14. Cluster formation and data communication • 1. Network model • Identical sensors uniformly distributed in the network • Location aware, maximum power is limited • Sink has sufficient resources

15. Cluster formation and data communication • 2. Cluster setup

16. Cluster formation and data communication • 3. Data Communication

17. Equalizing cluster lifetime ai ai-1 aibj-1 ai-1bj-1 bj-1 bj aibj ai-1bj

18. Maintaining CHs at the centre area of the cluster • 1. Intra-cluster communication: Cluster lifetime is separated into two periods: Period 1 only selects the node in the central area as a CH; Period 2 selects the node with the maximum residual energy in the cluster as a CH.

19. Maintaining the CHs at the centre area of the cluster • 2. Inter-cluster communication

20. Outline • Introduction • Existing energy-efficient clustering algorithms for sensor networks • Proposed clustering algorithm • Simulation • Simulation scenario • What is assessed • Results • Conclusion

21. Simulation scenario • Compared algorithms • Same size, single hop route / multi-hop route (LEACH_C_F, SS) • Scenario • 200 nodes within 100m*200m • Maximum transmission range: 140m • Data packet size: 500Byte • Initial energy per node: 5J • Sink is 10m away from the network

22. What is assessed • 1. First-node lifetime and network lifetime • First node lifetime: The time when any node dies • Network lifetime: • When the connectivity between the sink and the network is lost in a multi-hop clustered sensor network • When certain percentage (50%) of nodes die in a single hop clustered sensor network • 2. Distribution of residual node energy at network lifetime • 3. Packets delivered to the sink

23. Results • 1-1. First-node lifetime • Data aggregation rate λ: Every 1 bit will output λ (<1) bits after data aggregation • One round of data collection: Each time the network sends the aggregated data to the sink

24. Results • 1-2. Network Lifetime

25. Results • 1-3. Improvement of lifetime

26. Results • 2. Distribution of residual node energy at network lifetime

27. Results • 3-1. Total delivered network data up to network lifetime

28. Results • 3-2. Improvement in delivering data

29. Results • 3-3. Partial-network data: the data from part of the network so that they do not cover the information of the entire network

30. Outline • Introduction • Existing energy-efficient clustering algorithms for sensor networks • Proposed clustering algorithm • Simulation • Conclusion

31. Conclusion • The existing clustering algorithms for sensor networks are investigated • A clustering algorithm is proposed, which: • balances power consumption throughout the network by taking the directional data traffic into account • improves energy efficiency for homogeneous sensor networks • improves network performance by preventing any node from dying prematurely

32. Thanks for attention! Questions?