INTELLIGENT HEED ALGORITHM FOR ENERGY OPTIMIZATION IN HETEROGENOUS WIRELESS SENSOR NETWORK

Abstract

Sensors nodes with far distance from the Base Station tends to lose energy faster compare to those closer to it. Power consumption at such sensor nodes can be classified into four categories: communication, sensing, inactive listening, and data processing. Considering these four categories, communication (transmission and reception of data) prove to be a dominant feature in determining the rate of power consumption. Several routing protocols have been developed for energy drainage in communication. It has however been established that energy conservation is one of the key solutions to challenges posed by resource constrained wireless sensor networks (WSNs). Recent works are therefore on energy efficient protocols being applied on specific challenges. This research proposes a novel energy optimization algorithm called I-HEED (Intelligent Hybrid Energy Efficient Distributed) clustering which is an hybrid of HEED and Monkey Search Algorithm. This algorithm utilizes the optimized energy distribution method among sensor nodes in HEED protocol and optimization strategy in Monkey Search Algorithm to select the best cluster head. To ensure that the cluster head has enough capacity to transmit collaborative information from other sensor nodes to the base station. The result analysis shows that the I-HEED algorithm out performs LEACH (Low Energy Adaptive Clustering Hierarchy), DEEC (Distributed Energy Efficient Clustering) and HEED algorithm in terms of alive nodes, dead nodes and packet sent to the base station which are major determinant of energy optimization in WSN. The developed I-HEED algorithm performed 330% better than DEEC, 315 % better than HEED and 50% better than LEACH. I-HEED algorithm for WSNs provide energy efficient solution within resource constrained environments