Detection and avoidance of black-hole attack in mobile adhoc network using bee-ad-hoc on-demand distance vector

Abstract

Mobile adhoc networks (MANETs) are self-configuring networks with a dynamic infrastructure suit for real world applications. Due to the exponential increase in the network devices an efficient routing algorithm for dynamic network adhering the security issues is a critical challenge needs to be addressed. This article attempts to address this issue with the implemention of ad-hoc on-demand distance vector (AODV) routing approach, which is the best of its kind in the dynamic network design of MANETs. The primary goal is to address security attack weaknesses through the implementation of dynamic topologies and reactive routing. To this end, a bio-inspired swarm intelligence algorithm called Bees algorithm is used to emulate the AODV technique. In order to provide a lightweight solution that integrates the Bee algorithm and AODV routing, this study presents a unique algorithm called Bee-AODC. The proposed Bee-AODC algorithm possess the both the AODV's dynamic topology construction capabilities and the Bee algorithm's foraging strategy which effectively address security weaknesses by creating a dynamic network topology for ad hoc routing. By using the suggested Bee-AODC algorithm instead of the traditional AODV routing method, throughput is increased by 12.87% while packet loss, latency, and energy consumption are reduced by 20%, 40%, and 18%, respectively.