Sensor deployment strategy for target detection
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Minimizing communication costs in hierarchically-clustered networks of wireless sensors
Computer Networks: The International Journal of Computer and Telecommunications Networking
How to distribute sensors in a random field?
Proceedings of the 3rd international symposium on Information processing in sensor networks
A Minimum Cost Heterogeneous Sensor Network with a Lifetime Constraint
IEEE Transactions on Mobile Computing
Spatio-temporal sampling rates and energy efficiency in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
QoM and lifetime-constrained random deployment of sensor networks for minimum energy consumption
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
General Network Lifetime and Cost Models for Evaluating Sensor Network Deployment Strategies
IEEE Transactions on Mobile Computing
On the lifetime of wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
Relay Node Deployment Strategies in Heterogeneous Wireless Sensor Networks
IEEE Transactions on Mobile Computing
IEEE Transactions on Signal Processing
Optimal Node Density for Detection in Energy-Constrained Random Networks
IEEE Transactions on Signal Processing - Part II
Error Exponents for the Detection of Gauss–Markov Signals Using Randomly Spaced Sensors
IEEE Transactions on Signal Processing - Part I
MAC Essentials for Wireless Sensor Networks
IEEE Communications Surveys & Tutorials
Statistical location detection with sensor networks
IEEE Transactions on Information Theory
MAC protocols for wireless sensor networks: a survey
IEEE Communications Magazine
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We determine the optimal nonuniform spatial density of nodes in a single-hop Wireless Sensor Network (WSN) whose task is the distributed detection of a target within its sensing field. The optimization approach accounts for such factors as the Medium Access Control (MAC) protocol being used, the wireless channel's propagation characteristics, a randomized sleep/wake-up scheduling protocol, network coverage constraints, the energy consumed, the time to reach a decision, and the number of nodes in the network. The node density that minimizes the average Decision Error Probability (DEP) when a node at the center of the network serves as the Cluster Head (CH) is shown to be a function of the distance from this CH. The solution of this optimization problem and simulations demonstrate both the significant performance improvement provided by nonuniform spatial densities and the trade-offs that are possible amongst energy, network lifetime, detection performance, and time to reach a decision.