Name
Abstract | ||
|---|---|---|
The primary challenges in outlining and arranging the operations of wireless sensor networks are to enhance energy utilization and the system lifetime. Clustering is a powerful approach to arranging a system into an associated order, load adjusting and enhancing the system lifetime. In a cluster based network, cluster head closer to the sink depletes its energy quickly resulting in hot spot problems. To conquer this issue, numerous algorithms on unequal clustering are contemplated. The drawback in these algorithms is that the nodes which join with the specific cluster head bring overburden for the cluster head. So, we propose an algorithm called fuzzy based unequal clustering in this paper to enhance the execution of the current algorithms. The proposed work is assessed by utilizing simulation. The proposed algorithm is compared with two algorithms, one with an equivalent clustering algorithm called LEACH and another with an unequal clustering algorithm called EAUCF. The simulation results using MATLAB demonstrate that the proposed algorithm provides better performance compared to the other two algorithms. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s11276-015-1013-1 | Wireless Networks |
Keywords | Field | DocType |
Cluster head,Fuzzy logic,Fuzzy inference system,Residual energy,Unequal clustering,Wireless sensor network | Data mining,Canopy clustering algorithm,Fuzzy clustering,CURE data clustering algorithm,Data stream clustering,Correlation clustering,Computer science,FLAME clustering,Constrained clustering,Cluster analysis | Journal |
Volume | Issue | ISSN |
22 | 3 | 1022-0038 |
Citations | PageRank | References |
46 | 1.29 | 28 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| R. Logambigai | 1 | 80 | 4.01 |
| Arputharaj Kannan | 2 | 323 | 37.50 |