Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Probabilistic Coverage in Wireless Sensor Networks
LCN '05 Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary
Movement-Assisted Sensor Deployment
IEEE Transactions on Mobile Computing
Energy-efficient connected-coverage in wireless sensor networks
International Journal of Sensor Networks
Wireless sensor network survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Q-Coverage Problem in Wireless Sensor Networks
ICDCN '09 Proceedings of the 10th International Conference on Distributed Computing and Networking
A probabilistic model of k-coverage in minimum cost wireless sensor networks
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
QoS-aware target coverage in wireless sensor networks
Wireless Communications & Mobile Computing
Algorithmic challenges for sensor networks: foreword to ALGOSENSORS 2007
ALGOSENSORS'07 Proceedings of the 3rd international conference on Algorithmic aspects of wireless sensor networks
Redeploying mobile wireless sensor networks with virtual forces
WD'09 Proceedings of the 2nd IFIP conference on Wireless days
Efficient Coverage Maintenance Based on Probabilistic Distributed Detection
IEEE Transactions on Mobile Computing
Hi-index | 0.24 |
One of the main operations in wireless sensor networks is the surveillance of a set of events (targets) that occur in the field. In practice, a node monitors an event accurately when it is located closer to it, while the opposite happens when the node is moving away from the target. This detection accuracy can be represented by a probabilistic distribution. Since the network nodes are usually randomly deployed, some of the events are monitored by a few nodes and others by many nodes. In applications where there is a need of a full coverage and of a minimum allowed detection accuracy, a single node may not be able to sufficiently cover an event by itself. In this case, two or more nodes are needed to collaborate and to cover a single target. Moreover, all the nodes must be connected with a base station that collects the monitoring data. In this paper we describe the problem of the minimum sampling quality, where an event must be sufficiently detected by the maximum possible amount of time. Since the probability of detecting a single target using randomly deployed static nodes is quite low, we present a localized algorithm based on mobile nodes. Our algorithm sacrifices a part of the energy of the nodes by moving them to a new location in order to satisfy the desired detection accuracy. It divides the monitoring process in rounds to extend the network lifetime, while it ensures connectivity with the base station. Furthermore, since the network lifetime is strongly related to the number of rounds, we propose two redeployment schemes that enhance the performance of our approach by balancing the number of sensors between densely covered areas and areas that are poorly covered. Finally, our evaluation results show an over 10 times improvement on the network lifetime compared to the case where the sensors are static. Our approaches, also, outperform a virtual forces algorithm when connectivity with the base station is required. The redeployment schemes present a good balance between network lifetime and convergence time.