Research On Mobile Agent Based Routing Protocol In Wireless Sensor Networks

Wireless Sensor Network (WSN) is a self-organizing network with a large number of sensors, and has been used in many areas including military surveillance, environment monitoring. Since the resources, especially energy on sensor node, in WSN is limited, it is important to design energy-efficient routing protocol for WSN.This thesis presents basic knowledge on WSN, including concept, feature and key research issues. It analyzes advantages and disadvantages of typical flat and hierarchical routing protocols. Then, it investigates the design of four components in mobile agent for WSN, including architecture, itinerary planning, middleware design and multiple agents' cooperation. This paper also describes data fusion based mobile agent for WSN and discusses the routing planning algorithms in designing mobile agent.The thesis studies flat WSN with multi-types sensors and sensors in network have different sampling frequencies. A group based mobile agent routing protocol (GMAR) is proposed for this kind of WSN. In GMAR, sink node first collects basic information of each sensor node, including sensor's location, type and sampling frequency, etc. Then, sink node divides sensors that can be visited in one agent itinerary into one group and determines the node visiting sequence for each sensor group using route planning algorithms. GMAR provides a fault-tolerant mechanism for mobile agent:when node failure occurs and mobile agent can't continue its task along the predetermined route, a route adjustment method is employed to correct the agent's migrating route. The route determined by sink node can ensure that the mobile agent consumes low energy when it migrates in WSN, while the route adjustment method helps mobile agent continue it task by revising its route and neglects the effect of failure node on its migration.The complexity and time delay in GMAR are analyzed. Simulation results show that GMAR can reduce energy consumption during agent migration effectively, balance load and maximize lifetime of the network, and enhance robustness of agent's migration.