Minimizing energy for wireless web access with bounded slowdown
Proceedings of the 8th annual international conference on Mobile computing and networking
The coverage problem in a wireless sensor network
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
μSleep: a technique for reducing energy consumption in handheld devices
Proceedings of the 2nd international conference on Mobile systems, applications, and services
Performance measurements of motes sensor networks
MSWiM '04 Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
On k-coverage in a mostly sleeping sensor network
Proceedings of the 10th annual international conference on Mobile computing and networking
The holes problem in wireless sensor networks: a survey
ACM SIGMOBILE Mobile Computing and Communications Review
Integrated coverage and connectivity configuration for energy conservation in sensor networks
ACM Transactions on Sensor Networks (TOSN)
On computing conditional fault-tolerance measures for k-covered wireless sensor networks
Proceedings of the 9th ACM international symposium on Modeling analysis and simulation of wireless and mobile systems
An optimal node scheduling for flat wireless sensor networks
ICN'05 Proceedings of the 4th international conference on Networking - Volume Part I
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This paper presents the robustness and performance analysis of the Controlled Greedy Sleep algorithm, which was designed to provide k-coverage in wireless sensor networks. The aim of this algorithm is to prolong network lifetime while ensuring QoS requirements in a dynamic manner. We investigated how the network can be strenghtened to improve performance characteristics, and how this algorithm ensures graceful degradation (i.e., how the network will provide less accurate measurement data as sensors become unavailable). We also test the robustness of the algorithm by measuring the effect of message loss due to communication errors. We compare the results to those of a very known and frequently used random algorithm. Our performance tests are based on simulations results.