A coverage-preserving node scheduling scheme for large wireless sensor networks
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
PEAS: A Robust Energy Conserving Protocol for Long-lived Sensor Networks
ICNP '02 Proceedings of the 10th IEEE International Conference on Network Protocols
Differentiated surveillance for sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Set k-cover algorithms for energy efficient monitoring in wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms
Proceedings of the 3rd international symposium on Information processing in sensor networks
Optimization: Insights and Applications (Princeton Series in Applied Mathematics)
Optimization: Insights and Applications (Princeton Series in Applied Mathematics)
Random Coverage with Guaranteed Connectivity: Joint Scheduling for Wireless Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
A survey of energy-efficient scheduling mechanisms in sensor networks
Mobile Networks and Applications
Lightweight deployment-aware scheduling for wireless sensor networks
Mobile Networks and Applications
IEEE Transactions on Parallel and Distributed Systems
Intrusion Objects with Shapes under Randomized Scheduling Algorithm in Sensor Networks
ICDCSW '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops
Computer Networks: The International Journal of Computer and Telecommunications Networking
Coverage and Detection of a Randomized Scheduling Algorithm in Wireless Sensor Networks
IEEE Transactions on Computers
Primate-Inspired Communication Methods for Mobile and Static Sensors and RFID Tags
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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Wireless sensor networks consist of a large number of sensors and have been broadly used for intrusion detection in surveillance systems. To guarantee detection quality, such networks are usually over-engineered, i.e., more than required sensors are deployed and remain active in order to cover each point in the monitored field with a high probability at any time instance. Existing sensor scheduling schemes based on the point coverage model tightly weave a sensor "net" that is unnecessarily dense. Intuitively, when the size and the shape of intrusion objects are considered, any net with holes no smaller than the size of the intrusion object would work fine. With this design philosophy in mind, we build a new mathematical model to investigate the impact of size and shape of intrusion objects on network configuration. We derive analytical results that provide practitioners with insights on how to weave an effective sensor "net" for intrusion object detection with minimum number of active sensors.