ACSA: An Improved Ant Colony Algorithm for Routing Problems of Wireless Sensor Networks

Due to long calculation time and slow convergence speed, ant colony system (ACS) cannot be used directly in wireless sensor networks (WSN). In this paper, we present an improved ACS algorithm based on Altitude Information (AI) and Ant Withdrawal (AW), named ACSA (an improved ACS algorithm with AI). The concept of AI is defined, and the design philosophy, algorithm realization and performance simulation of ACSA are discussed. AI is a kind of global heuristic information correlated with the source and destination node, represents the possibility of ants traveling from current node to destination. With AI, the algorithm can get faster convergence speed; with AW, the algorithm can increase the probability of ants traveling to destination node, and avoid local optimization. The simulation of ACSA illustrates that ACSA can get more stable and robust result, faster calculation and convergence speed than ACS on the shortest route problems of WSN.