RITISH AGGARWAL

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RITISH AGGARWAL

  1. 1. CLUSTRING IN WIRELESS SENEOR NETWORK SEMINAR SUBMITTED IN PARTIAL FULLFILLMENT OF THE REQUIREMENT FOR THE AWARD OF THE DEGREE OF MASTER OF TECHNOLOGY (Computer Science and Engineering) Submitted by:- Ritish Aggarwal 1269170 (M.tech CSE) L.L.R.I.E.T. MOGA
  2. 2. CONTENTS  Wireless Sensor Network  Clustering  Objective of Clustering  Classification of Clustering  Routing Models  Clustering Algorithms  Hot Spot Problem  Energy Efficient Unequal Clustering  Comaprisons Of EEUC with Other Algorithms  Conclusion  Future Work  References
  3. 3. WHAT IS WIRELESS SENSOR NETWORK?  WSN consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure etc.  Collaborative Network of small Wireless Sensor devices, sensing a physical phenomenon.  Formed by hundreds or thousands of nodes that communicate with each other and pass data along from one to another.
  4. 4. ARCHITECTURE OF A WIRELESS SENSOR NETWORK
  5. 5. SENSORS ARRANGEMENT
  6. 6. APPLICATIONS
  7. 7. WHAT IS CLUSTERING ?? The process of organizing objects into groups whose members are similar in some way.
  8. 8. OBJECTIVE  Minimize the energy dissipation of the network.  Increase the network life time.  Clusters must be better balanced.  Better distribution of cluster heads in the network.
  9. 9. CLASSIFICATION OF CLUSTERING  Dominating-set-based clustering  Low-maintenance clustering  Mobility-aware clustering  Energy-efficient clustering  Load-balancing clustering  Combined-metrics-based clustering
  10. 10. WHAT IS CLUSTERING IN WIRELESS SENSOR NETWORK ????
  11. 11. MAIN COMPONENTS IN CLUSTERING  Clusters  Cluster Heads  Base Station  Sensor nodes
  12. 12. WHY CLUSTERING??  Reduce routing table size.  Conserve communication bandwidth.  Avoids redundant message exchanges.  Cluster head can aggregate data.  Clusters can schedule activities so sensors can sleep.
  13. 13. APPLICATIONS OF CLUSTERING  Marketing  Biology  Libraries  City-planning  Earthquake studies  WWW
  14. 14. ROUTING PROTOCOLS  Location–Base Protocol  Data-Centric Protocol  Hierarchical Routing Protocol
  15. 15. ROUTING MODELS IN CLUSTERING  Single –Hop  Multi-Hop
  16. 16. HOT SPOT PROBLEM  In single-hop communication:- Every sensor node will directly transmit the data to the base station, so the nodes furthest away from the base station are the most critical nodes.  In multi-hop communication:-Due to the limited transmission range, data’s are forced to route over several hops until they reach the final destination nodes that are closest to the base station are burdened with heavy relay traffic and they die first.
  17. 17. SOLUTION OF HOT SPOT PROBLEM EECU:- Energy- Efficient Unequal Clustering Algorithm In EECS a distance-based cluster formation method is proposed to produce clusters of unequal size in single hop networks. A weighted function is introduced to let clusters farther away from the base station have smaller sizes, thus some energy could be preserved for long-distance data transmission to the base station.
  18. 18. ENERGY- EFFICIENT UNEQUAL CLUSTERING (EEUC)  EEUC partitions the nodes into Clusters of Unequal size, and Clusters closer to the Base Station have smaller sizes than those farther away from the base station.  Thus Cluster heads closer to the base station can preserve some energy for the inter-cluster data forwarding.[4]
  19. 19. EEUC MECHANISM
  20. 20. ENERGY SAVING SCHEMES IN CLUSTERING TECHNOLOGY  Cluster Formation and Rotation  Cluster Head Election and Rotation  K-Hops Approach
  21. 21. WORKING OF EEUC EECU Initial Diagram
  22. 22. BASIC BLOCK DIAGRAM
  23. 23. CLUSTERING ALGORITHMS  LEACH (Low Power Adaptive Clustering Hierarchy)  HEED(Hybrid Energy Efficient Distributed )  GAF  WCA (Weighted Clustering Algorithm)  K-MEANS (K-Hop Clustering Algorithm)
  24. 24. LEACH  It uses circular random clustering methods and each node in the network can be a cluster head in rotation, this makes the energy- carrying of the network balancing to each node, extending the lifetime of the network.
  25. 25. BASIC BLOCK DIAGRAM
  26. 26. DISADVANTAGE OF LEACH 1.Applicable to only single hop communication mode. 2.LEACH assumes all the nodes to have same initial energy, which is not the case always in real-time problems. 3.It cannot be applied for mobile nodes, failure of cluster-heads creates a lot of problems
  27. 27. COMPARISONS OF EECU WITH WCAALGORITHM  WCA:-WCA is a classical algorithm based on node degree, the number of single-hop neighbours.  MAIN DRAWBACK :- The main drawback of WCA is that it needs to obtain the weight of the node and require each node to save all the information of nodes before initializing network, so excessive amounts of computing and communications may cause excessive consumption in clustering directly.
  28. 28. K-CLUSTERING ALGORITHMS  K-clustering algorithm can constitute maximum k- hop non-overlapping clusters with partial networks topology information rather than the whole network topology. At the same time, it can also save energy to prolong network survival time.  PROBLEM :-The algorithm is more effective in restricting data forwarding distance, but it still doesn’t solve unbalanced clustering (excessive clustering nodes).
  29. 29. CONCLUSION Result shows that our unequal clustering mechanism balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime.
  30. 30. REFERENCES [1] Kazem Sohraby, Daniel Minoli, Taieb Znati “WIRELESS SENSOR NET- WORKS Technology, Protocols, and Applications” John Wiley, New York, 2007. [2] S.Mohanty and S.K.Patra,“A novel Bio-inspired Clustering algorithm for Wireless Sensor Network (ICIAS 2010). [3] O. Younis,M Krunz, S. Ramasubramanian “Node clustering in wireless sensor networks: Recent developments and deployment challenges”, IEEE May 2006. [4] Chengfa Li, Mao Ye, “An Energy-Efficient Unequal Clustering Mechanism for Wireless Sensor Networks” [5] Ying Liao, Huan Qi, and Weiqun Li “Load-Balanced Clustering Algorithm With Distributed Self-Organization for Wireless Sensor Networks ”IEEE May 2013. [6] W. R. Heinzelman A. P. Chandrakasan and H. Balakrishnan “Energy- efficient communication protocol for wireless micro sensor networks” [7] H. C. Lin and Y. H. Chu, “A clustering technique for large multihop mobile wireless networks, May 2000 [8] Chengfa Li, Mao Ye, Jie Wu “An Energy-Efficient Unequal Clustering Mechanism for Wireless Sensor Networks”

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