Authors : Venu Madhav Kuthadi and Tshilidzi Marwala
Abstract: In Wireless Sensor Networks (WSNs), the major problem in multiple sinks is efficient data collection and scheduling which can be overcome by aggregated tree construction and TDMA based scheduling technique. Earlier, the techniques used for aggregated tree construction process takes more iteration to complete entire process which maximizes the scheduling delay. Therefore, there is need of an efficient aggregated tree construction which reduces the wastage of iteration time. In this study, we propose energy Efficient Multi-swarm fruit fly Optimization (EMO) algorithm for scheduling. In our EMO, the multi-swarm fruit fly optimization technique is applied in Pocket Driven Trajectories (PDT) to minimize the delay and save energy. Then Breadth First Search (BFS) algorithm is used for time slot scheduling process. The proposed EMO algorithm reduces the iteration time to maximize the aggregated tree construction speed. The simulations show that the proposed EMO algorithm significantly reduces the data collection delay and energy consumption.
Venu Madhav Kuthadi and Tshilidzi Marwala, 2017. Energy Efficient EMO Algorithm Based Scheduling Technique in Wireless Sensor Networks. Asian Journal of Information Technology, 16: 816-824.