Habitat monitoring: application driver for wireless communications technology
SIGCOMM LA '01 Workshop on Data communication in Latin America and the Caribbean
Proceedings of the 8th annual international conference on Mobile computing and networking
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Sensors and Wireless Communication for Medical Care
DEXA '03 Proceedings of the 14th International Workshop on Database and Expert Systems Applications
A distributed energy aware routing protocol for wireless sensor networks
PE-WASUN '05 Proceedings of the 2nd ACM international workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
Energy-Efficient Data Aggregation Hierarchy for Wireless Sensor Networks
Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks
On the upper bound of α-lifetime for large sensor networks
ACM Transactions on Sensor Networks (TOSN)
Maximum Lifetime of Sensor Networks with Adjustable Sensing Range
SNPD-SAWN '06 Proceedings of the Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Energy efficient real-time data aggregation in wireless sensor networks
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Improving network lifetime using sensors with adjustable sensing ranges
International Journal of Sensor Networks
Unreliable sensor grids: coverage, connectivity and diameter
Ad Hoc Networks
Coverage problems in sensor networks: A survey
ACM Computing Surveys (CSUR)
Hi-index | 0.00 |
In wireless sensor networks, nodes may employ multiple sensing modalities to improve the robustness of covering a region. Multi-modality coverage requires that every point in the region be covered by at least one node for each sensing modality. In this paper, we study the problem of maximizing the multi-modality coverage time and the relationship between node density and the probability of coverage. To this end, for the coverage time, we (1) derive lower and upper bounds on the achievable coverage time; (2) formulate the multi-modality coverage time maximization problem as a linear program; and (3) develop a heuristic to compute the achievable coverage time when the network is operated in phases. Through simulations, we show that the heuristic approach attains coverage time close to the optimal for a random network when large number of phases are employed. For the node density estimation, we evaluate the probability that a point is covered by at least one node for each modality for a given density of deployment by considering the possible correlation in the sensed information.