Coverage restoration of wireless sensor networks through the usage of decision trees
AsiaCSN '07 Proceedings of the Fourth IASTED Asian Conference on Communication Systems and Networks
On barrier resilience of sensor networks
ALGOSENSORS'11 Proceedings of the 7th international conference on Algorithms for Sensor Systems, Wireless Ad Hoc Networks and Autonomous Mobile Entities
PECA: Power Efficient Clustering Algorithm for Wireless Sensor Networks
International Journal of Information Technology and Web Engineering
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Wireless sensor networks (WSN) promise to revolutionize the way we monitor our surroundings by enhancing our senses. Prototype systems are already being demonstrated. Several fundamental research issues, however, remain unaddressed. Sensing events being the main task of a WSN, appropriately addressing the issue of coverage is critical. In this dissertation, we make a two fold contribution on establishing a strong foundation for the issue of coverage. First, we argue that a single concept of coverage such as k-full coverage (where every point in the deployment region needs to be within the monitoring range of at least k sensors) does not fit all applications. We propose a new concept of coverage called k-barrier coverage that is appropriate for intrusion detection applications. A WSN provides k-barrier coverage if it guarantees that every penetrating object is detected by at least k sensors before crossing the barrier of sensors. Second, we address five foundational problems for the issue of k-barrier coverage: optimal deployment pattern, critical conditions, coverage status determination, coverage restoration, and optimal sleep wakeup. The problem of optimal deployment pattern is to determine a pattern of deployment that uses the minimum number of sensors. The problem of critical conditions is to derive conditions that can be used to determine the minimum number of sensors to deploy in probabilistic deployments. The problem of coverage status determination is to determine whether a deployed WSN provides a desired quality of monitoring. The problem of coverage restoration is to determine the minimum number of sensors to deploy, and their locations, such that a desired quality of monitoring can be restored in a deployed WSN. The problem of optimal sleep wakeup is to produce a sleeping schedule for sensors that maximizes the network lifetime. We comprehensively solve four of the five foundational problems. For the problem of critical conditions, we derive the conditions for a weaker notion of k-barrier coverage, called weak k-barrier coverage. In addition, we derive critical conditions for the case of k-full coverage.