Abstract: Network lifetime plays an integral role in setting up an efficient wireless sensor network. The objectives of this thesis are: 1) To deploy sensor nodes at optimal locations such that the theoretically computed network lifetime is maximum 2) To schedule these sensor nodes such that the network attains the maximum lifetime. 3) A coverageaware sensor deployment scheme should be developed to ensure sufficient sensing coverage, and 4) to face of sensing node failures, a sensor self-organizing mechanism needs to be devised to efficiently recover the sensing void and restore the required sensing coverage. Since local repairs generally consume less moving energy and communication overhead than a global redeployment does, the sensor self-organizing mechanism should limit the network recovery/repairing locally to effectively reduce unnecessary. Further, the nodes are scheduled to achieve this upper bound. This project uses artificial bee colony algorithm and particle swarm optimization for sensor deployment problem followed by a heuristic for scheduling. In addition, ANT colony optimization technique is used to provide maximum network lifetime utilization. The comparative study shows that artificial ACO performs better than bee colony algorithm for sensor deployment problem. The proposed heuristic was able to achieve the theoretical upper bound in all the experimented cases.
Keywords: UWSN, Sensor Deployment, Energy Hole, Sensor Scheduling, ABC algorithm, ANT Colony Algorithm, PSO algorithm.