Multiple Ant Colony Routing Optimization Based on Cloud Model for WSN with Long-Chain Structure

Recent developments in the field of transmission line monitoring system have led to a renewed interest in wireless sensor networks, which is characterized by the strong real time, high reliability, adaptability, load balancing and so on. However, the bottleneck problem of network transmission which is likely to occur around the sink node must be taken into account. This paper proposes a new cross-layer routing algorithm for wireless sensor networks-multiple ant colony routing optimization algorithm based on cloud model. Through the interaction of pheromone between populations, the routing algorithm searches for the feasible paths in parallel and updates the pheromone timely. In the path-finding process, the routing metrics of single-hop delay, hop count, queue length and packet reception rate are regarded as heuristics correction factor. Multiple rules generator is used to optimize the residual factor ρ and the total pheromone information Q so as to update the pheromone adaptively. 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 the congestion control mechanism.