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Author Looga, V. ♦ Zhonghong Ou ♦ Yang Deng ♦ Antti-Yla-Jaaski
Sponsorship IEEE
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science ♦ Technology ♦ Engineering & allied operations
Subject Keyword Wireless communication ♦ Energy consumption ♦ Adaptation models ♦ Microcontrollers ♦ Computational modeling ♦ Receivers ♦ Hardware
Abstract Large wireless sensor networks (WSNs) with thousands of motes are expected to be a significant part of the future connected world. As battery life of such motes is still an issue, it is important to provide scalable methods to estimate energy usage without introducing significant overhead. We foresee that in the future significant amount of data will be collected and inferred on the behavior of motes. Such collection and inference of data can be considered as a virtual representation of the physical mote, with a potentially longer life-cycle. The virtual mote is a valuable resource for application development, diagnostics and behavior prediction. In this paper, we focus on the energy consumption aspect of such motes. To that end, we develop a packet-based real-time energy model, which works by analyzing network traffic traces collected at the backend to estimate energy consumption of the mote. Such approach scales well to the number of motes and does not require modification to the mote or its network stack. Experimental results from extensive measurements conducted on two platforms, i.e., OpenMote and Zolertia Z1, demonstrate promising potential. The energy model can achieve an estimation accuracy over 90% for platform power, and over 85% accuracy for radio power consumption, on various scenarios.
Description Author affiliation: Sch. of Sci., Dept. of Comput. Sci. & Eng., Aalto Univ., Espoo, Finland (Looga, V.; Zhonghong Ou; Yang Deng; Antti-Yla-Jaaski)
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-10-19
Publisher Place United Arab Emirates
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781467377010
Size (in Bytes) 1.03 MB
Page Count 8
Starting Page 716
Ending Page 723

Source: IEEE Xplore Digital Library