Low energy operation in WSNs: A survey of preamble sampling MAC protocols
Computer Networks: The International Journal of Computer and Telecommunications Networking
An asynchronous scheduler to minimize energy consumption in wireless sensor networks
NEW2AN'11/ruSMART'11 Proceedings of the 11th international conference and 4th international conference on Smart spaces and next generation wired/wireless networking
Joint queue and sleep control for energy-efficiency and delay guarantees in wireless sensor networks
Proceedings of the 2012 ACM Research in Applied Computation Symposium
ACM Transactions on Sensor Networks (TOSN)
A game theory distributed approach for energy optimization in WSNs
ACM Transactions on Sensor Networks (TOSN)
A cooperative pursuit-evasion game in wireless sensor and actor networks
Journal of Parallel and Distributed Computing
Duty-cycle optimization for IEEE 802.15.4 wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
Journal of High Speed Networks
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Energy efficiency is of the utmost importance in wireless sensor networks. The family of Low-Power-Listening MAC protocols was proposed to reduce one form of energy dissipation—idle listening, a radio state for which the energy consumption cannot be neglected. Low-Power-Listening MAC protocols are characterized by a duty cycle: a node probes the channel every t_i{\rm s} of sleep. A low duty cycle favors receiving nodes because they may sleep for longer periods of time, but at the same time, contention may increase locally, thereby reducing the number of packets that can be sent. We propose two new approaches to control the duty cycle so that the target rate of transmitted packets is reached, while the consumed energy is minimized. The first approach, called asymmetric additive duty cycle control (AADCC), employs a linear increase/linear decrease in the t_i value based on the number of successfully received packets. This approach is easy to implement, but it cannot provide an ideal solution. The second approach, called dynamic duty cycle control (DDCC) utilizes control theory to strike a near-optimal balance between energy consumption and packet delivery successes. We generalize both approaches to multihop networks. Results show that both approaches can appropriately adjust t_i to the current network conditions, although the dynamic controller (DDCC) yields results closer to the ideal solution. Thus, the network can use an energy saving low duty cycle, while delivering up to four times more packets in a timely manner when the offered load increases.