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POSE.R: Prediction-based Opportunistic Sensing for Resilient and Efficient Sensor Networks

Published: 25 November 2020 Publication History

Abstract

The article presents a distributed algorithm, called Prediction-based Opportunistic Sensing for Resilient and Efficient Sensor Networks (POSE.R), where the sensor nodes utilize predictions of the targets' positions to probabilistically control their multi-modal operating states to track the targets. There are two desired features of the algorithm: energy efficiency and resilience. If the target is traveling through a high-node-density area, then an optimal sensor selection approach is employed that maximizes a joint cost function of remaining energy and geometric diversity around the target’s position. This provides energy efficiency and increases the network lifetime while preventing redundant nodes from tracking the target. However, if the target is traveling through a low-node-density area or in a coverage gap (e.g., formed by node failures or non-uniform node deployment), then a potential game is played amongst the surrounding nodes to optimally expand their sensing ranges via minimizing energy consumption and maximizing target coverage. This provides resilience, that is, the self-healing capability to track the target in the presence of low node densities and coverage gaps. The algorithm is comparatively evaluated against existing approaches through Monte Carlo simulations that demonstrate its superiority in terms of tracking performance, network-resilience, and network-lifetime.

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cover image ACM Transactions on Sensor Networks
ACM Transactions on Sensor Networks  Volume 17, Issue 1
February 2021
256 pages
ISSN:1550-4859
EISSN:1550-4867
DOI:10.1145/3426429
Issue’s Table of Contents
© 2020 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the United States Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Publication History

Published: 25 November 2020
Accepted: 01 August 2020
Revised: 01 May 2020
Received: 01 October 2019
Published in TOSN Volume 17, Issue 1

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  1. Distributed sensor networks
  2. network lifetime
  3. network resilience

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  • (2022)TESS: multivariate sensor time series prediction for building sustainable smart citiesACM Transactions on Sensor Networks10.1145/3573200Online publication date: 8-Dec-2022

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