Shanmugasundaram Thilagavathi
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Shanmugasundaram Thilagavathi has a total of 1 co-authors. Here are the top co-authors by number of shared publications:
Bhavani Gnanasambandan Geetha
Department of Computer Science and Engineering, K. S. Rangasamy College of Technology, Tiruchengode, Tamilnadu 637 215, India
1 shared publication
Latest Publications
- Open Access
- 1 January 2015
- Published by Wiley in The Scientific World Journal
- Vol. 2015 (1) , 395256
Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network
Wireless sensor networks (WSNs) are emerging as a low cost popular solution for many real‐world challenges. The low cost ensures deployment of large sensor arrays to perform military and civilian tasks. Generally, WSNs are power constrained due to their unique deployment method which makes replacement of battery source difficult. Challenges in WSN include a well‐organized communication platform for the network with negligible power utilization. In this work, an improved binary particle swarm optimization (PSO) algorithm with modified connected dominating set (CDS) based on residual energy is proposed for discovery of optimal number of clusters and cluster head (CH). Simulations show that the proposed BPSO‐T and BPSO‐EADS perform better than LEACH‐ and PSO‐based system in terms of energy savings and QOS.
- 1 January 2015
- Published by Wiley in The Scientific World Journal
- Vol. 2015 (1) , 395256
Open AccessEnergy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network
Wireless sensor networks (WSNs) are emerging as a low cost popular solution for many real‐world challenges. The low cost ensures deployment of large sensor arrays to perform military and civilian tasks. Generally, WSNs are power constrained due to their unique deployment method which makes replacement of battery source difficult. Challenges in WSN include a well‐organized communication platform for the network with negligible power utilization. In this work, an improved binary particle swarm optimization (PSO) algorithm with modified connected dominating set (CDS) based on residual energy is proposed for discovery of optimal number of clusters and cluster head (CH). Simulations show that the proposed BPSO‐T and BPSO‐EADS perform better than LEACH‐ and PSO‐based system in terms of energy savings and QOS.