Randomized algorithms
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Geography-informed energy conservation for Ad Hoc routing
Proceedings of the 7th annual international conference on Mobile computing and networking
Proceedings of the 7th annual international conference on Mobile computing and networking
Distributed Algorithms
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
The Impact of Data Aggregation in Wireless Sensor Networks
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
Performance evaluation and enhancement of surface coverage relay protocol
NETWORKING'08 Proceedings of the 7th international IFIP-TC6 networking conference on AdHoc and sensor networks, wireless networks, next generation internet
Multiple coverage with controlled connectivity in wireless sensor networks
Proceedings of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
ACM Transactions on Sensor Networks (TOSN)
Wireless Sensor Node Placement Using Hybrid Genetic Programming and Genetic Algorithms
International Journal of Intelligent Information Technologies
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This work considers a multi-hop sensor network and addresses the problem of minimizing power consumption in each sensor node locally while ensuring two global (i.e., network wide) properties: (i) communication connectivity, and (ii) sensing coverage. A sensor node saves energy by suspending its sensing and communication activities according to a Markovian stochastic process. We show that a power level to induce a coverage radius w(n)/n is sufficient for connectivity provided that w(n) → ∞. The paper presents a Markov model and its solution for steady state distributions to determine the operation of a single node. Given the steady state probabilities, we construct a non-linear optimization problem to minimize the power consumption. Simulation studies to examine the collective behavior of large number of sensor nodes produce results that are predicted by the analytical model.