The Key Research On Self-Organizing Management Technologies For Wireless Sensor Networks

Wireless sensor networks(WSNs) is a distributed technology for sensing and collecting environment information, consisting of large numbers of small, low-powered, wireless"motes"each with limited computation, sensing, and communication ability. However, since there are lots of unpredictable conditions in WSNs and its environment, WSNs must possess the perfect capability of self-organizing management so that the network can reconstruct or reconfigure itself automatically, harmonize the resource allocation and task scheduling effectively, and transmit data flow by using apporiate protocols or algorithms.With the trait of moving computation to data, the mobile agent technology brings a new idea for the distributed system design. Therefore, by introducing the mobile agent into WSNs and absorbing the ideas of microeconomics and game theory, a deep and systematic research work is done in this thesis to design the mobile agent-based self-organizing management technologies with focus on the mobile agent model, the optimization of resource & task, the transmiting and collecting of data flow.For the mobile agent model, this thesis analyses the mobile agent-based computing model and compares it with the client/sever-based computing model, designs the mobile agent middleware which supports the application framework of WSNs with the mobile agent's architecture. For the problem of mobile agent route, a static routing method is design to search an optimal route with genetic algorithm, and the dynamic route method is also discussed.For the self-organizing management on resource and task, this thesis designs a self-organizing microeconomic system in which the application tasks are scheduled onto nodes by mobile agents while distribute their resource consumption across network. Further, it proposes the market-based resource allocation policy named MRA which satisfies the optimal division of the single capacity for multiple tasks. For harmonizing the resource allocation and task scheduling, it also proposes a market-based task scheduling policy named MTS which schedules tasks to the set of optimal nodes.For the self-organizing management on data flow, this thesis provides a cooperative solution for data transmiting and collecting. For data collecting, it proposes a resolution based parallel quantizing overlapping algorithm named RPQO to execute the distributed data fusion. For data transmiting, it proposes a pareto optimal utility based packet forwarding algorithm named POUPF which constitutes a Nash Equilibrium. Also, a subgame perfect method is achieved in the repeated game of packet forwarding.The achievements of the research work in this thesis can be used to support other key technologies of WSNs. And it can also be used in the applications with the requirements of real-time and dynamic adaptation, such as target tracking.