부산대학교 도서관

Due to small size, low cost, and many other attractive features of sensor nodes, wireless sensor networks (WSNs) have been adapted to a vast array of applications in both military and civil sectors, such as military surveillance, smart homes, and remote environment monitoring.Modern day requirements of various applications ecessitate large scale sensor deployment in as efficient a way as possible. In this thesis we investigate the problem of increasing the sensor network’s sense and detect sensitivity in both space and time. All of the existing literature surveyed as part of this research indicates that all of the solutions address singular aspects of this problem. My research is novel in that I address this problem holistically. The research goal is to maximize coverage and minimize energy consumption in sensor deployment and self-organization in WSNs.The thesis first introduces a comprehensive taxonomy for WSNs deployment and selforganization. Three sensor relocation algorithms are proposed to match the mobility degree of sensor nodes, particle swarm optimization based algorithm (PSOA), relay shift based algorithm (RSBA) and energy efficient fuzzy optimization algorithm (EFOA). PSOA regards the sensors in the network as a swarm, and reorganizes the sensors by the particle swarm optimization (PSO) algorithm, in the full sensor mobility case. RSBA and EFOA assume relatively limited sensor mobility to further reduce energy consumption. We propose a novel method for the redeployment of mobile nodes in a hybrid sensor network consisting of a collection of both static nodes and mobile nodes. In such a sensor network, the locomotion ability of mobile nodes helps the autonomous deployment to enhance the network coverage. An optimal decision of a sensor node moving direction is made based on Analytical Hierarchy Process (AHP). Four factors contributing to the optimal deployment are onsidered and they are coverage hole, obstacle avoidance, hot spot, and the boundary effect, respectively. I also propose a network maintenance strategy in the post-deployment phase based on the sensor node importance level ranking. Simulation results show that our approach not only achieves fast and stable deployment but also greatly improves the network coverage and prolongs the lifetime.In order to enable efficient self-organiztion in static sensor networks, I propose a VQ-LBG based approach for cluster formation in WSNs. The most distinguishing feature of the proposed method is that both energy efficient cluster formation and fast data compression can be guaranteed. Experiment shows its great improvement over other related methods. The thesis then presents a sleep scheduling scheme for balancing energy consumption rates in a single hop cluster based network using AHP. Three factors are considered contributing to the optimal nodes scheduling decision and they are the distance to cluster head, residual energy, and sensing coverage overlapping, respectively. I also propose an integrated sleep scheduling and routing scheme for WSNs by AHP. The sleep scheduling is redesigned to adapt the multi-hop case. For the proposed routing protocol, the distance to the destination location, remaining battery capacity, and queue size of candidate sensor nodes in the local communication range are taken into consideration for next hop relay node selection.In summary, this thesis provides an important link between the crucial problems of coverage, connectivity, energy management, and self-organization in wireless sensor networks. It is expected to lead to even more efficient protocols for node deployment, state management, recovery and routing protocols for energy-constrained sensor networks.