TinyBee: Mobile agent based data gathering system in wireless sensor networks

Scope and Method of Study. The thesis proposes the mobile-agent-based data-gathering system in sensor networks from a new point of view. The objectives of the thesis are: (1) Studying concepts of mobile agents and previous research related to the thesis; (2) Exploring data-gathering system under a specific situation where a server is movable in sensor networks; (3) Making the system time-efficient as well as energy-efficient enough; (4) Simulating the system with appropriate data settings; (5) Experimenting, analyzing results, and evaluating the proposed system. The execution time and the consumed energy are performance metrics of the system by comparing to the traditional server/client model. In simulation experiments, we change the number of sensor nodes, the size of mobile agents, and a kind of network protocols in order to analyze effects of such parameters on the system.;Findings and Conclusions. We designed data gathering system using a special kind of mobile agents called TinyBee to successfully collect data all over the network. TinyBee migrates from node to node after dispatched from a mobile server like a robot. We also introduced two kinds of network protocols called MMCBR and LEAR-AODV in order to let TinyBee returns to the robot energy-efficiently. The system was precisely evaluated with a simulator called NetLogo. Simulation experiments showed that our TinyBee based model is not only both time-efficient and energy-efficient, but also scalable rather than a traditional server/client based model. In addition to analyzing performance improvement between the server/client based model and the TinyBee based model, we also investigated performance difference between the TinyBee based model using MMCBR protocol and the model using LEAR-AODV protocol. Experiments showed using LEAR-AODV is a superior solution than using MMCBR in terms of distribution of energy residual on sensor nodes.