WSN Partitioning Strategies vu final project cs619 help

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WSN Partitioning Strategies vu final project cs619 help

Wireless Sensor Network is partitioned into collection of nodes which are called clusters. Clustering technique is used in order to enhance performance of WSNs. There are many clustering techniques whose goals are longevity, convergence in more area, nodes reliability and route stability. CH may be pre-selected by network designer or elected by sensors in clusters after deployment. CHs are mainly responsible for all activities in the clusters like it keeps member nodes in low power sleep mode to increase the life time of individual node by reducing the energy consumption.

Different energy efficient routing protocols have been suggested which perform single and multi hop communication to send data from source to cluster head and cluster head to sink(base station) like following:

1. CACC: Clustering Algorithm based on Cell Combination 
2. VAP-E: Energy-Efficient Clustering -Virtual Area Partition 
3. CFL: Clustering for Localization 
4. FoVs: Overlapped Field of View 
5. KOCA: K-Hop Overlapping Clustering Algorithm
6. PEZCA: Power-Efficient Zoning Clustering Algorithm 
7. VoGC: Voting-on-Grid clustering 
8. BARC: Battery Aware Reliable Clustering
9. Hausdroff Clustering 
10. HSA: Harmony Search Algorithms 
11. PEGASIS: Power-Efficient Gathering in Sensor Information System 
12. Max-Min D-Cluster Algorithm 
13. PDCH: Pegasis Algorithm Improving Based on Double Cluster Head 
14. GROUP 
15. EECS: Energy Efficient Clustering Schemes 
16. EEUC: Energy Efficient Unequal Clustering
17. LCA: Linked Cluster Algorithms and LCA2 
18. Highest-connectivity cluster algorithm
19. Particle swarm optimizers for cluster formation in wireless sensor networks (PSO- Clustering )
20. PSO-C: Centralized-PSO 
21. MST-PSO: Minimum Spanning Tree-PSO 
22. LEACH and Its Descendant

Students will simulate suggested clustering protocols and compare the result with the respect to energy consumption and life time of nodes in WSN.

Simulations can be implemented in MATLAB or any network simulation like NS2 etc.

NOTE: Students will implement and compare result of any two algorithms specified by the Supervisor.

Supervisor: Tanweer Arshad (a...@vu.edu.pk)
Application Type: Desktop Application
Possible Students: 1 to 2
Proposed Tools: MATLAB, Any network similar (NS2 etc.)

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