Maximal Lifetime Scheduling for Sensor Surveillance Systems with K Sensors to One Target
IEEE Transactions on Parallel and Distributed Systems
Some problems of directional sensor networks
International Journal of Sensor Networks
Localized Sensor Area Coverage with Low Communication Overhead
IEEE Transactions on Mobile Computing
Randomized Approach for Target Coverage Scheduling in Directional Sensor Network
ICESS '07 Proceedings of the 3rd international conference on Embedded Software and Systems
Establishing Trust Beliefs Based on a Uniform Disposition to Trust
SITIS '07 Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System
Improving Lifetime and Coverage through Mobile Beacon for High Density Sensor Networks
SENSORCOMM '08 Proceedings of the 2008 Second International Conference on Sensor Technologies and Applications
Hilbert mobile beacon for localisation and coverage in sensor networks
International Journal of Systems Science - Networked Control Systems and Wireless Sensor Networks - Theories and Applications
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Traditional vision systems for surveillance applications are built essentially from distributed high resolution video cameras and powerful processing units which communicate in general with central servers via a high bandwidth network. Using autonomous and small wireless video sensor nodes can add a much higher level of flexibility, therefore extending the range of surveillance applications that could be considered and, more interestingly, can support dynamic deployment scenario. With such resource-constrained devices power conservation is an important issue but one must also ensure that the application's objectives are met. In this paper, we address the problem of adaptive scheduling of sensor node's activity to extend the network lifetime while fulfilling a critical surveillance application needs. We first present a distributed algorithm that ensures both coverage of the deployment area and network connectivity by providing multiple cover sets to manage Field of View redundancies. Then, we propose a multiple levels activity model that uses behavior functions modeled by modified Bezier curves to define application classes and allow for adaptive scheduling. Simulation results are presented to validate the performance of the proposed approach.