Paper Title:Energy Efficient Wireless Sensor Networks using Swarm Intelligence based Clustering and Data Aggregation: A Survey


The Wireless Sensor Networks (WSN’s) are the need of today’s world in variety of applications. IoT and Fog are being the emerging and popular areas of application and research have sensor network as their basic foundation. The major research challenges in designing an IoT and Fog Computing based applications are to have the reduction in energy consumption, secured and aggregated data transmission, Routing, Handling massive scaling of IoT network, Handling Heterogeneous devices and platforms etc. Proper design of WSN plays an important role to deal with these issues. In literature many approaches are suggested and already implemented to handle the issue of energy efficiency in WSN. This paper gives the survey different types of swarm intelligence algorithms and explains how they are useful in wireless sensor network. The aim of this paper is to discuss in brief about the Swarm intelligence algorithms, to highlight the importance Particle Swarm Intelligence in clustering in WSN, to survey some of the techniques used previously for clustering, routing and data aggregation, and explains how PSO can be used in Clustering to reduce the energy consumption and balance the network load. Clustering is a non-deterministic polynomial time (NO) hard problems in WSN [1]. PSO particle swarm organization can be used to find fast and effective solutions in clustering and cluster head selection. Proper clustering, selection of good routing mechanism, effective data aggregation scheme can significantly reduce the energy consumption of the network and leads to increase in the life time of the network. [10]

Keywords:WSN, Energy Optimization, Swarm Intelligence, Clustering, Data Aggregation.