Cloud model and ant colony optimization based qos routing algorithm for wireless sensor networks

Abstract

This paper presents CMACRO (Cloud Model and Multiple Ant Colonies Optimization based Routing), a new cross-layer QoS routing algorithm for wireless sensor networks. Basing on the principle of cross-layer design, the algorithm adapts delay, nodes' load and link quality as QoS metrics, and provides differentiated services for real time event-driven data streams and delay-tolerant periodic sampling data. The QoS routing metrics are regarded as heuristics correction factors in ant colony algorithm (ACA). The ants are divided into a number of different populations. Through the interaction of pheromone between multi populations, the routing algorithm searches for the feasible paths in parallel and updates the pheromone in time. To overcome the slow convergence of ant colony algorithm, improvements to control the randomness of the ants via cloud model are proposed. The simulation results demonstrate that the routing algorithm can guarantee the real time, reliability and robustness of wireless sensor networks. It can also achieve the network load balancing and congestion control mechanism. © 2012 Springer-Verlag Berlin Heidelberg.