Adaptive duty-cycling based on group size for energy balance of sensor nodes in wireless sensor networks

Cha, Myungsu; Kim, Mihui; Kim, Moonseong; Choo, Hyunseung

doi:10.1145/2103380.2103409

Cited by 3 publications

(1 citation statement)

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“…[55] present optimal solutions for throughput maximization for the offline case with consideration of storage losses due to the battery imperfections. A group size based approach to adaptively manage the duty cycle of sensor nodes is proposed to prolong network lifetime in [12].…”

Section: Related Workmentioning

confidence: 99%

Energy management for age of information control in solar-powered IoT end devices

Aydin

Akar

2021

Wireless Netw

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In this paper, we propose several harvesting-aware energy management policies for solar-powered wireless IoT end devices that asynchronously send status updates for their surrounding environments to a network gateway device. For such devices, we aim at minimizing the average age of information (AoI) metric which has recently been investigated extensively for status update systems. The proposed energy management policies are obtained using discrete-time Markov chain-based modeling of the stochastic intra-day variations of the solar energy harvesting process in conjunction with the average reward Markov decision process formulation. With this approach, energy management policies are constructed by using the time of day and month of year information in addition to the instantaneous values of the age of information and the battery level. The effectiveness of the proposed energy management policies in terms of their capability to reduce the average AoI as well as improving upon the tail of the AoI distribution, is validated with empirical data for a wide range of system parameters.

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Section: Related Workmentioning

confidence: 99%