Adaptive Self-Healing in Mobile Networks Using Levy Flight-Based Bat Algorithm

In this research, an adaptive self-healing mechanism for mobile networks is proposed which uses an Lévy Flight-Based Bat Algorithm (LFBA). Even though by inserting the Lévy flights the nature of the Bat Algorithm is improved, by offering better exploration through the solution space, the proposed method returns optimum results in a shorter time span for fault recovery. In order to evaluate the performance of the proposed LFBA in different scenarios of the network, the algorithm was examined and compared with the existing approaches for different sizes of the network and the number of flows as well as for different levels of offered load comprising 37. It applies a more heuristical-like basis of altering the fault recovery time by 5%, the network throughput by 15%, and energy consumption that is 25% lesser than the norms set by traditional algorithms. From the above findings, it is revealed that the LFBA can respond to the requirements of enhancing network robustness and dependability.