PEAS: A Robust Energy Conserving Protocol for Long-lived Sensor Networks
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Impact of radio irregularity on wireless sensor networks
Proceedings of the 2nd international conference on Mobile systems, applications, and services
Versatile low power media access for wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
A Minimum Cost Heterogeneous Sensor Network with a Lifetime Constraint
IEEE Transactions on Mobile Computing
Worst and Best-Case Coverage in Sensor Networks
IEEE Transactions on Mobile Computing
Integrated coverage and connectivity configuration for energy conservation in sensor networks
ACM Transactions on Sensor Networks (TOSN)
Barrier coverage with wireless sensors
Proceedings of the 11th annual international conference on Mobile computing and networking
Maintaining differentiated coverage in heterogeneous sensor networks
EURASIP Journal on Wireless Communications and Networking
Connected sensor cover: self-organization of sensor networks for efficient query execution
IEEE/ACM Transactions on Networking (TON)
Stochastic coverage in heterogeneous sensor networks
ACM Transactions on Sensor Networks (TOSN)
Distributed protocols for ensuring both coverage and connectivity of a wireless sensor network
ACM Transactions on Sensor Networks (TOSN)
Clustering-based minimum energy wireless m-connected k-covered sensor networks
EWSN'08 Proceedings of the 5th European conference on Wireless sensor networks
Analysis of target detection performance for wireless sensor networks
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Coverage in wireless ad hoc sensor networks
IEEE Transactions on Computers
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Sensing coverage is a performance metric that reflects the quality of surveillance of a field by a wireless sensor network. This paper investigates the problem of minimum connected k-coverage in homogeneous and heterogeneous wireless sensor networks, where each point in a field is covered (or sensed) by at least k active nodes while minimizing the necessary total number of active nodes and guaranteeing connectivity between them. First, we study the case of homogeneous nodes to gain some insights on how to address the problem of k-coverage using heterogeneous nodes. Our methodology to solve the minimum connected k-coverage problem consists of two main phases: sensing range slicing and active node scheduling. The goal of the slicing phase is to decompose the sensing range of a sensor node into smaller, congruent regions such that each of them is guaranteed to be k-covered when exactly k nodes are deployed in it. The purpose of the scheduling phase is to specify which nodes turn on (or become active), how, and when. In this paper, we propose two k-coverage protocols using different scheduling approaches. In the first protocol, called self-scheduling driven k-coverage, each sensor node turns itself on based on the local information it has about its sensing neighbors in order to k-cover its sensing range. The second protocol, called triggered-scheduling drivenk-coverage, allows a sensor node to trigger a necessary number of its sensing neighbors to become active in order to achieve k-coverage of its sensing range. Then, to promote the use of self-scheduling driven k-coverage and triggered-scheduling driven k-coverage in real-world sensing applications, we show how to relax some commonly used assumption for coverage configuration protocols in wireless sensor networks. More specifically, we discuss a more general framework, where the nodes are heterogeneous in terms of their sensing ranges. Precisely, we propose two protocols for k-coverage using heterogeneous nodes and generalize them by considering convex sensing and communication models. Simulation results show that triggered-scheduling driven k-coverage outperforms self-scheduling driven k-coverage with regard to the number of nodes required for connected k-coverage configuration as well as the network lifetime. We find that self-scheduling driven k-coverage outperforms an existing connected k-coverage protocol for wireless sensor networks. Also, we find that heterogeneity has a positive impact on our k-coverage protocol performance.