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
Dynamic deployment in ad hoc networks accommodating uncertain transmission range
Proceedings of the 9th ACM international symposium on Mobility management and wireless access
Dynamic deployment in ad hoc networks accommodating uncertain transmission range
Proceedings of the 9th ACM international symposium on Mobility management and wireless access
| Hi-index | 0.00 |
Proposals for optimal network deployment in wireless ad hoc/sensor networks generally seek to meet specific performance objectives (e.g., connectivity and coverage), typically assuming known and constant transmission ranges for nodes at different geographic locations and in different directions. In practice transmission range is highly uncertain a priori, even for homogeneous networks. In our prior paper, we explored physical layer models for estimating node connectivity in linear networks, where network nodes are all arranged along a ray, taking into consideration the lognormal distribution and spatial correlation of signal strength. We examined application in linear network deployment, in which an agent (e.g., a robot) would be responsible for maximizing the probability of connecting all sensing nodes given limited network resources: (i) the number of available routing nodes and (ii) the linear time/distance that can be operated by the agent for deploying the network. Though theoretically the dynamic programming framework we developed for linear deployment in our prior work could be easily extended to address planar deployment problems, it would easily become computational intractable even for a small planar network. This paper proposes a heuristic to extend its application for planar deployment when the transmission range is short and uncertain compared to the separate distances of sensing nodes. The heuristic involves two steps, the first of which is to construct a tree spreading all the sensing nodes, while the second is to deploy routing nodes along the edges of the tree, taking advantage of the developed heuristic for linear deployment in our prior work. Numerical examples are provided to illustrate its applications and performances.