DocumentCode
3105807
Title
Duty cycling and power management with a network of energy harvesting sensors
Author
Reddy, Srinivas ; Murthy, Chandra R.
Author_Institution
Dept. of ECE, Indian Inst. of Sci., Bangalore, India
fYear
2011
fDate
13-16 Dec. 2011
Firstpage
205
Lastpage
208
Abstract
In this paper, we study duty cycling and power management in a network of energy harvesting sensor (EHS) nodes. We consider a one-hop network, where K EHS nodes send data to a destination over a wireless fading channel. The goal is to find the optimum duty cycling and power scheduling across the nodes that maximizes the average sum data rate, subject to energy neutrality at each node. We adopt a two-stage approach to simplify the problem. In the inner stage, we solve the problem of optimal duty cycling of the nodes, subject to the short-term power constraint set by the outer stage. The outer stage sets the short-term power constraints on the inner stage to maximize the long-term expected sum data rate, subject to long-term energy neutrality at each node. Albeit suboptimal, our solutions turn out to have a surprisingly simple form: the duty cycle allotted to each node by the inner stage is simply the fractional allotted power of that node relative to the total allotted power. The sum power allotted is a clipped version of the sum harvested power across all the nodes. The average sum throughput thus ultimately depends only on the sum harvested power and its statistics. We illustrate the performance improvement offered by the proposed solution compared to other naive schemes via Monte-Carlo simulations.
Keywords
Monte Carlo methods; energy harvesting; fading channels; scheduling; wireless sensor networks; Monte-Carlo simulations; average sum data rate maximization; average sum throughput; energy harvesting sensor nodes; long-term energy neutrality; long-term expected sum data rate; naive schemes; one-hop network; optimum duty cycling; power management; power scheduling; short-term power constraint; wireless fading channel; Batteries; Energy harvesting; Resource management; Sensors; Throughput; Wireless communication; Wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2011 4th IEEE International Workshop on
Conference_Location
San Juan
Print_ISBN
978-1-4577-2104-5
Type
conf
DOI
10.1109/CAMSAP.2011.6135983
Filename
6135983
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