PAMAS—power aware multi-access protocol with signalling for ad hoc networks
ACM SIGCOMM Computer Communication Review
Asynchronous wakeup for ad hoc networks
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
An adaptive energy-efficient MAC protocol for wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Latency of wireless sensor networks with uncoordinated power saving mechanisms
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
Maximum lifetime routing in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Sleep/Active Schedules as a tunable characteristic of a Wireless Sensor Network
ICNS '06 Proceedings of the International conference on Networking and Services
An Analytical Model for Wireless Sensor Networks with Sleeping Nodes
IEEE Transactions on Mobile Computing
An Energy-Efficient Dynamic Power Management in Wireless Sensor Networks
ISPDC '06 Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing
Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks
IEEE Transactions on Information Theory
IEEE Communications Magazine
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Wireless sensor networks are currently deployed in many areas, particularly for surveillance related applications. Sensors have very limited energy and processing capabilities, hence, it becomes necessary to introduce energy efficient algorithms to maximize the lifetime of a sensor node. We propose a new scheduling scheme based on Discrete Time Markov chain models used in genetics for DNA evolution prediction. The proposed scheduler uses a single control parameter to control state changes in order to obtain a compromise between network lifetime and throughput. We discuss the design of such a Discrete Time Markov chain based scheme and compare it to a standard approach in terms of node throughput and lifetime of entire network. Finally, we show the effectiveness of this scheme by simulating various network topologies in a realistic sensor network. Our observations show that just after 75% of simulation steps 90% more nodes are alive with the proposed scheduler. The residual battery power is 82% more and the packet reception rate is increased by 51% for the entire network when compared to the standard approach.