The Multi-Objective Routing Optimization of WSNs Based on an Improved Ant Colony Algorithm

At present most of the WSNs routing protocol only have a single research objective. The overall network performance lacks of multi-objective inspection and evaluation. The basic task of multi-objective routing is to find a route in the network which has sufficient resources to optimize some network parameters and satisfy multiple constrains. A multi-objective model, constrained of bandwidth, is put forward, which optimizes function such as energy consumption, network delay and data packet lost rate. By adjusting the weight of each function, the algorithm adapts well to various services whose requirements for energy cost, delay and lost are different. As it is difficult to optimize multi-objective problem, an advanced ant colony algorithm based on cloud model (AACOCM) is proposed, which can effectively restrict the algorithm to falling in local best. Simulation results show that this novel method has a certain validity and feasibility and be able to adapt to different services requirements.