Journal Article10.1109/TNET.2009.2032294
Minimizing delay and maximizing lifetime for wireless sensor networks with anycast
TL;DR: The proposed solution to the joint control problem of how to optimally control the system parameters of the sleep-wake scheduling protocol and the anycast packet-forwarding protocol to maximize the network lifetime can outperform prior heuristic solutions in the literature.
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Abstract: In this paper, we are interested in minimizing the delay and maximizing the lifetime of event-driven wireless sensor networks for which events occur infrequently. In such systems, most of the energy is consumed when the radios are on, waiting for a packet to arrive. Sleep-wake scheduling is an effective mechanism to prolong the lifetime of these energy-constrained wireless sensor networks. However, sleep-wake scheduling could result in substantial delays because a transmitting node needs to wait for its next-hop relay node to wake up. An interesting line of work attempts to reduce these delays by developing "anycast"-based packet forwarding schemes, where each node opportunistically forwards a packet to the first neighboring node that wakes up among multiple candidate nodes. In this paper, we first study how to optimize the anycast forwarding schemes for minimizing the expected packet-delivery delays from the sensor nodes to the sink. Based on this result, we then provide a solution to the joint control problem of how to optimally control the system parameters of the sleep-wake scheduling protocol and the anycast packet-forwarding protocol to maximize the network lifetime, subject to a constraint on the expected end-to-end packet-delivery delay. Our numerical results indicate that the proposed solution can outperform prior heuristic solutions in the literature, especially under practical scenarios where there are obstructions, e.g., a lake or a mountain, in the coverage area of the wireless sensor network.
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Citations
A survey of network lifetime maximization techniques in wireless sensor networks
TL;DR: The family of NL maximization techniques is introduced, the portrayal of rich variety definitions of NL design objective used for WSNs, and some design guidelines with examples are provided to show the potential improvements of the different design criteria.
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TL;DR: The proposed approach, based on the reinforcement learning technique, enables each node to autonomously decide its own operation mode (sleep, listen, or transmission) in each time slot in a decentralized manner.
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A Survey on an Energy-Efficient and Energy-Balanced Routing Protocol for Wireless Sensor Networks.
TL;DR: An extensive survey of the different state-of-the-art energy-efficient and energy-balanced routing protocols for WSNs is presented and possible research directions in order to optimize the energy consumption in sensor networks are suggested.
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An Energy Efficient Routing Protocol for Wireless Sensor Networks using A-star Algorithm
TL;DR: A new energy-efficient routing protocol (EERP) has been proposed for WSNs using A- star algorithm and results indicate that the proposed scheme improves network lifetime in comparison with A-star and fuzzy logic(A&F) protocol.
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Sensor Placement with Multiple Objectives for Structural Health Monitoring
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