Long term sensing via battery health adaptation
File(s)PID4733117.pdf (266.08 KB)
Accepted version
Author(s)
Jackson, G
Qin, Z
mccann, J
Type
Conference Paper
Abstract
Energy Neutral Operation (ENO) has created the ability to continuously operate wireless sensor networks in areas such as environmental monitoring, hazard detection and industrial IoT applications. Current ENO approaches utilise techniques such as sample rate control, adaptive duty cycling and data reduction methods to balance energy generation, storage and consumption. However, the state of the art approaches makes a strong and unrealistic assumption that battery capacity is fixed throughout the deployment time of an application. This results in scenarios where ENO systems over allocate sensing tasks, therefore as battery capacity degrades it causes the system to no longer be energy neutral and then fail unexpectedly. In this paper, we formulate the problem to maximise the quality-of-service in terms of duty cycle and the battery capacity to extend the deployment lifetime of a sensing application. In addition, we develop a lightweight algorithm to solve the formulated problem. Moreover, we evaluate the proposed method using real sensor energy consumption data captured from micro-climate sensors deployed in Queen Elizabeth Olympic Park, London. Results show that a 307% extension of deployment lifetime can be achieved when compared to a traditional ENO solution without a reduction in the duty cycle of the sensor.
Date Issued
2017-07-17
Date Acceptance
2017-03-17
Citation
2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), 2017, pp.2240-2245
Publisher
IEEE
Start Page
2240
End Page
2245
Journal / Book Title
2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)
Copyright Statement
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Intel Corporation
Grant Number
CODSE_P61388
Source
IEEE International Conference on Distributed Computing Systems (ICDCS 2017)
Subjects
Science & Technology
Technology
Computer Science, Theory & Methods
Computer Science
ENERGY MANAGEMENT
SYSTEM
Publication Status
Published
Start Date
2017-06-05
Finish Date
2017-06-08
Coverage Spatial
Atlanta, USA
Date Publish Online
2017-07-17