A Novel Adaptive Bio-Inspired Clustered Routing for MANET

Abstract

MANET (Mobile Ad-hoc Network) is a mobile multi-hop wireless self-organized distributed ad-hoc network thatdoes not require the basic internal construction. Routing in MANET is a challenging problem which draws researcher's vision, due to nodes mobility, dynamic topology and lack of central point like base station or servers. Clustering of devices in MANET could reduce overhead, flooding and collision in communication and make the network topology more stable. The ABC (Artificial Bee Colony) algorithm is a new meta-heuristic population based optimization technique inspired by the intelligent foraging behavior of honeybee swarms. In this paper, a new general framework has been proposed for achieving QoS which provides a cluster based routing and applies Artificial Bee Colony optimization Technique for effective optimal route discovery in MANET. It works on the principle of collective intelligence and emergence of artificial honey bees. It's application in ad-hoc networks involves swarming agents (honey bees) hopping node to node, analyzing a set of variables exposed by the nodes and provide the optimal path and minimize the routing overhead and also provides QoS guarantees with an ability for minimal end-to-end delay and enhanced scalability.