An energy and delay aware optimal data aggregation using three fold algorithm for WSN

Abstract

Wireless sensor networks (WSNs) have been regarded as an emerging and promising field in several applications like facility, health, environmental monitoring, military survival lance and target tracking. Due to their unique characteristics such networks suitable for those real-time applications, such as ease deployment, handling and self-organisation. The technical challenges in terms of energy and delay are need to address here and data aggregation is basic solution to solve those problems by forward useful data's to destination. However, the data and connection loss occurs in the data forwarding, here we propose energy and delay aware optimal data aggregation (EDODA). We make three main contributions in EDODA method: firstly, we propose a new clustering technique using an improved swarm optimisation (ISO) algorithm to make balanced clusters, which minimise the energy consumption. Secondly, the modified multi-fruit fly optimisation algorithm (MFOA) is used to determine aggregated nodes (AN). Thirdly, we introduce a new searching method using fish-food search (FFS) algorithm based on the destination functional characteristics, which provides routing between source-destination. The results show that the improvement of proposed EDODA method in terms of delay, energy and network lifetime.