Paper Info
Title
Energy Harvesting WSNs for Accurately Estimating the Maximum Sensor Reading: Trade-offs and Optimal Design
Abstract
Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.
Year
DOI
Venue
2015
10.1109/TWC.2015.2422811
Wireless Communications, IEEE Transactions  
Keywords
Field
DocType
energy harvesting,fading,max function computation,quantization,wireless sensor networks,wireless communication,signal to noise ratio,schedules
Key distribution in wireless sensor networks,Wireless,Transmitter power output,Signal-to-noise ratio,Energy harvesting,Computer network,Real-time computing,Schedule,Wireless sensor network,Mathematics,Channel state information
Journal
Volume
Issue
ISSN
PP
99
1536-1276
Citations 
PageRank 
References 
1
0.38
23
Authors
2
Name
Order
Citations
PageRank
Shilpa Rao121.11
Neelesh B. Mehta297982.27