Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks
IEEE Transactions on Computers
Impact of radio irregularity on wireless sensor networks
Proceedings of the 2nd international conference on Mobile systems, applications, and services
Extremal Properties of Three-Dimensional Sensor Networks with Applications
IEEE Transactions on Mobile Computing
Models and solutions for radio irregularity in wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
ATPC: adaptive transmission power control for wireless sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Search-Oriented Deployment Strategies for Wireless Sensor Networks
ISORC '07 Proceedings of the 10th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing
Automatic and robust breadcrumb system deployment for indoor firefighter applications
Proceedings of the 8th international conference on Mobile systems, applications, and services
Ad hoc network deployment accommodating short and uncertain transmission range
Proceedings of the 9th ACM international symposium on Mobility management and wireless access
Ad hoc network deployment accommodating short and uncertain transmission range
Proceedings of the 9th ACM international symposium on Mobility management and wireless access
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Proposals for optimal network deployment in wireless ad hoc networks generally seek to meet specific performance objectives (e.g., connectivity and coverage), typically assuming known and constant transmission ranges for nodes at different locations and in different directions. In practice transmission range is highly uncertain a priori, even for homogeneous networks. In this paper, we explore physical layer models for estimating node connectivity in planar networks based on connectivity observations available from previously deployed nodes, taking into consideration the lognormal distribution and spatial correlation of signal strength. Then we examine application in deployment problems in which an agent (e.g., a robot) would be responsible for maximizing the probability of connecting all separate sensing nodes given a limited number of wireless routing nodes. Though theoretically the dynamic programming framework is suitable for addressing the deployment problem, it would easily become computational intractable even for a small-sized network. This paper proposes heuristics for the deployment problem involving two steps. We alternatively construct a network tree spreading all the separate sensing nodes, and then determine locations for placing routing nodes based on the constructed tree and available connectivity observations, until either the network is connected or the routing nodes are used up. Numerical examples are provided to illustrate the application and performance of the proposed heuristics.