EACO and FABC to multi-path data transmission in wireless sensor networks

Owing 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. In this study, the authors have developed a new algorithm called, exponential ant colony optimisation (EACO) to route discovery problem in wireless sensor network after finding the cluster heads (CHs) using fractional artificial bee colony (FABC) algorithm. In the first step, CHs 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 CHs to transmit a data from any source node to base station with multiple objectives including energy, distance, intra-cluster delay and intercluster delay. These objectives are effectively formulated as new fitness function to find the optimal route path. From the experimentation, the outcome showed that the cumulative energy kept after 2000 round of experiments is 0.2039 for the proposed algorithm but the existing approach (threshold + ACO) kept only 0.0338.