Exponential Ant Colony Optimization and Fractional Artificial Bee Colony to MultiPath Data Transmission in Wireless Sensor Networks

Due to the extensive growth of wireless technology for sending and collecting a variety of information for the different applications, routing is a major challenge to find the optimal path for the data transmission. Literature presents various works for data transmission using multipath routing to reduce the energy loss and distance. In this work, we have developed a new algorithm called, Exponential Ant Colony Optimization (EACO) to route discovery problem in WSN after finding the cluster heads using Fractional Artificial Bee Colony (FABC) algorithm. In the first step, cluster head are found out using the FABC algorithm with fitness function considering the distance, energy and delay. In the second phase, ACO algorithm is modified with Exponential Smoothing model for multi-path route discovery. This new algorithm called, EACO found the optimal routes among cluster heads to transmit a data from any source node to base station with multiple objectives including energy, distance, intra cluster delay and inter cluster delay. These objectives are effectively formulated as new fitness function to find the optimal route path. The performance of the proposed EACO-based multi-path routing protocol (FABC+EACO) for data transmission is compared with ABC+ACO, Threshold+ACO using life time, energy and goodput. The Page 1 of 27 IET Review Copy Only IET Communications This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication in an issue of the journal. To cite the paper please use the doi provided on the Digital Library page.