RITISH AGGARWAL
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Transcript of RITISH AGGARWAL
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
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
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.
ARCHITECTURE OF A WIRELESS SENSOR NETWORK
SENSORS ARRANGEMENT
APPLICATIONS
WHAT IS CLUSTERING ??
The process of organizing objects into groups whose members are similar in some way.
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.
CLASSIFICATION OF CLUSTERING
Dominating-set-based clustering
Low-maintenance clustering
Mobility-aware clustering
Energy-efficient clustering
Load-balancing clustering
Combined-metrics-based clustering
WHAT IS CLUSTERING IN WIRELESS SENSOR NETWORK ????
MAIN COMPONENTS IN CLUSTERING Clusters
Cluster Heads
Base Station
Sensor nodes
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.
APPLICATIONS OF CLUSTERING
Marketing
Biology
Libraries
City-planning
Earthquake studies
WWW
ROUTING PROTOCOLS
Location–Base Protocol Data-Centric Protocol Hierarchical Routing Protocol
ROUTING MODELS IN CLUSTERING
Single –Hop Multi-Hop
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.
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.
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]
EEUC MECHANISM
ENERGY SAVING SCHEMES IN CLUSTERING TECHNOLOGY
Cluster Formation and Rotation
Cluster Head Election and Rotation
K-Hops Approach
WORKING OF EEUC
EECU Initial Diagram
BASIC BLOCK DIAGRAM
CLUSTERING ALGORITHMS
LEACH (Low Power Adaptive Clustering Hierarchy)
HEED(Hybrid Energy Efficient Distributed )
GAF
WCA (Weighted Clustering Algorithm)
K-MEANS (K-Hop Clustering Algorithm)
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.
BASIC BLOCK DIAGRAM
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
COMPARISONS OF EECU WITH WCA ALGORITHM 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.
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).
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.
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”