Research On Key Techniques Of Wireless Sensor Network Based On Mobile Agent

Wireless sensor network (WSN) is a new type of application network, cross-integrate of several technologies such as sensor and wireless communication and so on. For a special method about acquiring and processing information of WSN, which make it widely used in intelligent traffic, intelligent architecture, envirotunent monitoring and national defense construct etc. Larger numbers,constrain energy and capacity about sensors in wireless sensor network, make energy management technology, clutering technology and routing technogy become a research hotspot and key technology in this field.This paper make a deeply investigate about those three key technology above. The main researeh work is as follows:1.In view of the insufficiency in the wireless sensor network energy management, the energy management strategy based on multiple mobile Agent of wireless sensor network is proposed, the multiple mobile Agent energy model is constructed, the multiple mobile Agent synergetic distributed task algorithm is introduced in the model, to reduce the delay, prolong the network life. The simulation results show that it is more energy efficient, less network delay than the LEACH and single mobile Agent energy management model.2.In view of wireless sensor network every round node energy consumption and node energy consumption of unbalanced problem in the clustering, the paper puts forward the mobile Agent based multilayer clustering algorithm, constructs multilayer clustering energy model, through the mobile Agent technology to the election of each round cluster head and collect each round data. The simulation results show that, compared with energy efficiency multilayer clustering and LEACH algorithm, Energy Efficiency Multilayer Clustering algorithm reduces the energy consumption per round, more balanced energy consumption and prolong the network life cycle.3.In view of wireless sensor networks mobile agent routing problem, mobile agent routing algorithm for wireless sensor networks based on Q learning hybrid with ant colony optimization is proposed. A new path choosing probability model is introduced and the optimal path is efficiently maintained in the algorithm. Simulation results show that the mobile agent routing efficiency is highly improved and delay requirements in multiple tasks is fulfiled, the reliability of the optimal path is enhanced, and network energy consumption is reduced.Above all, introduce the mobile Agent in the wireless sensor network can effectively solve the insufficiency in wireless sensor network in the aspect of energy management and the clustering. The Q learning is combined with ant colony optimization algorithm can effectively solve the problems existing in the wireless sensor network mobile Agent routing.