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PRESENTED BY, V.Rajasekaran. AD-HOC SENSOR NETWORK USING HYBRID ENERGY EFFICIENT DISTRIBUTED CLUSTERING.

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Presentation on theme: "PRESENTED BY, V.Rajasekaran. AD-HOC SENSOR NETWORK USING HYBRID ENERGY EFFICIENT DISTRIBUTED CLUSTERING."— Presentation transcript:

1 PRESENTED BY, V.Rajasekaran. AD-HOC SENSOR NETWORK USING HYBRID ENERGY EFFICIENT DISTRIBUTED CLUSTERING

2 INTRODUCTION Sensor networks have recently emerged as a platform for several important surveillance and control applications. The Sensor nodes are usually less mobile, more restricted in capabilities, and more thickly deployed than mobile ad- hoc networks (MANETs). This necessitates devising novel energy proficient solutions to some of the conventional wireless networking problems, such as routing, medium access control, self-organization, security and bandwidth allocation

3 SINGLE HOP WITH AND WITHOUT CLUSTERING

4 MULTI-HOP WITH AND WITHOUT CLUSTERING

5 CLUSTERING PROBLEM A node must be able to directly communicate with its cluster head (via a single hop). Cluster heads can make use of a routing protocol to compute inter- cluster paths for multi-hop communication to the observer(s). The following requirements must be met: 1) Clustering is entirely distributed. Each node independently makes its decisions based only on local information. 2) Clustering ends within a fixed number of iterations (regardless of network diameter). 3) At the end of each T CP, each node is either a cluster head, or not a cluster head (which we refer to as a regular node) that belongs to accurately one cluster.

6 3. THE HE 2 D PROTOCOL 3.1. Clustering Parameters it define the parameters used in the clustering process. 3.2 Protocol Operation it presents the protocol Operations

7 3.3 PSEUDOCODE HE 2 D protocol pseudo-code I. Initialize II. Repeat 1. S nbr {v: v lies within my cluster range} 1. If ((S CH {v: v is a cluster head})≠Ø) 2. Compute and broadcast cost to ε S nbr 2. My_ cluster _head least_ cost(S CH ) 3. CHprob max(Cprob × Eresidual/Emax, pmin) 3. If (my_ cluster head = NodeID) 4. is _final _CH FALSE 4. If (CHprob = 1) 5. Cluster head msg(NodeID,final _CH,cost) III. Finalize 6. Is_ final_ CH TRUE 1. If (is_ final_ CH = FALSE) 7. Else 2. If ((S CH {v: v is a final cluster head})≠Ø ) 8. Cluster_head _msg(NodeID, tentative _CH,cost) 3. my_ cluster head least cost(SCH) 9. ElseIf (CHprob = 1) 4. join _cluster(cluster_ head_ ID, NodeID) 10. Cluster_ head _msg(NodeID,final_ CH,cost) 5. Else Cluster_ head_ msg(NodeID, final _CH, cost) 11. Is_ final_ CH TRUE 6. Else Cluster_ head _msg(NodeID, final_ CH, cost) 12. ElseIf Random(0,1) < CHprob 13. Cluster_head _msg(NodeID,tentative_ CH,cost) 14. CHprevious CHprob 15. CHprob min(CHprob × 2, 1) Until CHprevious = 1

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