Energy-Efficient Coverage In Wireless Sensor Networks

Wireless Sensor Networks (WSNs), which are made viable by the convergence of micro-electro-mechanical system technology, wireless communications and digital electronics, have changed the way that human recognize and communicate with the physical nature. WSN is a self-organized distributed intelligent system comprising low-cost, low-power, multifunctional sensor nodes that are small in size and capable of wireless communication tethered in short distances. These tiny sensor nodes, which consist of sensing, data processing, and communicating components, leverage the idea of sensor networks based on collaborative effort of a large number of nodes. As a novel mode of computing and a hotspot of information technology after internet, Wireless Sensor Networks promise many new application areas, such as military applications, environmental applications, health application, home application and other commercial application.Coverage is vital and also fundamental in wireless sensor networks' research and applications, and has great influence on performance of the networks. Characteristics of sensor nodes such as large-scaled and dense deployment, constraints on power, communicating ability, computing ability and memory ability, and unattended infertile circumstance bring great challenges in network coverage. Focusing on the most efficient coverage of random distributed sensor nodes, collaborative coverage, multiple targets associative coverage and coverage adapting to the application physical nature, the dissertation studies on the coverage problems in wireless sensor networks. The major contribution of this dissertation is specifically stated as follows.(1) Research on wireless sensor networks coverage is surveyed, while the challenge in WSN coverage is analyzed. Network coverage evaluation system is proposed and design issue in WSN coverage is concluded.(2) Focusing on the coverage efficiency, the ideal optimal distribution is deduced in mobile sensor networks coverage. According to the ideal distribution, coverage-efficient coverage algorithm CEVFA is presented which is based on virtual force algorithm VFA, considering useless move, boundary and optimal moving distance etc.. Simulation results show that the performance of CEVFA is better than VFA.(3) In order to satisfy the different requirement of different interest point synchronously, a new coverage algorithm WMCA is proposed. WMCA is fit for WSN for its energy-efficiency and low computing complexity. It is the first coverage algorithm that providing different coverage service for different interest points synchronously till now.(4) In some application, a sensor node can not cover the object independently. Acollaborative coverage manner is presented to fulfill the application that only one sensor node cannot. Relationships among system collaborative coverage probability, the number of sensor nodes and the lowest coverage probability that nodes have to work are deduced in detail. The performance of collaborative coverage is analyzed with different sensor nodes distribution. An energy-adaptive collaborative coverage optimization algorithm CTCO is proposed, while the simulation results show that CTCO is able to improve the coverage quality and prolong the networks lifetime.(5) Mobile sensor nodes are introduced to obstructed and energy limited WSN coverage. Optimal relationship model is built considering collaborative coverage quality, moving distance and energy cost. Collaborative targets coverage optimization algorithm in mobile sensor networks CTCOMSN is presented. Simulation is done in obstacle coverage phenomena and circumstances that static nodes can not complete monitoring, and the results show that CTCOMSN is efficient in improving coverage quality and prolonging network lifetime. CTCOMSN can also be used in normal coverage.(6) For multiple target monitoring, several targets are monitored by a group of sensor nodes, while several sensor nodes are in charge of many targets. Relationship between them is complex, and there must be some association among nodes and targets. According to that association, multiple targets association coverage algorithm MTCAC is designed using association rule dining technology. Network lifetime is prolonged by transition of the work state of sensor nodes groups. Compared with advanced PEAS, MTCAC shows better coverage quality and longer lifetime. MTCAC is the first coverage algorithm in the view of association among nodes and targets, which illuminates other association research in WSN.(7) The location of sensor nodes can influence the coverage quality. To adapt sensor nodes to deployment of the physical characters, a novel coverage algorithm NGECA is presented. It is also the first algorithm in view of physical characters inside the monitored area, which is significant in other WSN research. Simulations have studied on influence of space grid and physical gradients, and whose results show that NGECA can provide high coverage quality with a few sensor nodes, while network resource is saved at the same time and robust and stability of WSN is increased.(8) In order to satisfy the real-time requirement in long-time environmental applications, a real-time NGECA is presented. Simulation results show that NGECA can quickly provide the physical information if the character varied in monitored area. It is a would-be 3D algorithm, and gives some ideas to the future real-time coverage research.