Routing Algorithm For Wireless Sensor Networks Based On Mobile Agent Model

Wireless sensor network with the high monitoring accuracy, strong dynamic stability, low cost, data-centric, strong system fault tolerance and other notable features is favored by people in every field, it has been used widely. However, the wireless sensor networks has limited energy, computing and storage capacity are weak, together with network bandwidth constraints, so the wireless sensor network communication speed is slow down, the ability of network data processing and transmission are weakened, and the consumption of the network energy is larger. Hence we need to design a better routing algorithm; it can reduce energy consumption, delay and enhance dynamic adaptability.In the design of wireless sensor networks routing algorithm, distributed computing model for mobile agent can reduce network latency and energy consumption, it has high adaptability and good scalability. Routing algorithm based on this model need to solve the access to which nodes and node path problem.In this paper, we use the clustering approach to solve the problem of access to which nodes and use genetic algorithm to solve the node path problem by studying home and abroad literature. Firstly, we propose a flower clustering algorithm, the algorithm used to optimize the wireless sensor network clustering, to determine the cluster head node. After clustering, we design a data fusion framework based on mobile agent, then combining fusion model, proposed a type of mobile agent routing algorithm based on improved adaptive genetic algorithm(Genetic MA Routing Algorithm, GMRA).This algorithm use improved adaptive genetic algorithm to find the best mobile agent migration path to traverse the cluster head node. Simulation results show that this method has some advantages, as the wireless sensor network size increases, the algorithm can effectively reduce energy consumption and network latency.