Engineering friendly tool to estimate battery life of a wireless sensor node

Battery life of low power devices is a major concern for the users of such devices. Existing research focuses on using different power management techniques and power consumption models to predict the battery life. However most of the exiting power consumption models and simulators assume a high deg...

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Published in:Journal of industrial information integration Vol. 4; pp. 8 - 14
Main Authors: Bag, Gargi, Pang, Zhibo, Johansson, Morgan E., Min, Xiaoyu, Zhu, Shaoling
Format: Journal Article
Language:English
Published: Elsevier Inc 01.12.2016
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ISSN:2452-414X, 2467-964X, 2452-414X
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Abstract Battery life of low power devices is a major concern for the users of such devices. Existing research focuses on using different power management techniques and power consumption models to predict the battery life. However most of the exiting power consumption models and simulators assume a high degree of technical expertise of the users such as user of a home automation system. This paper proposes a power consumption model that can be used as an easy to use engineering tool by the end user or system integrators to estimate the battery life of the device by just estimating the levels related to expected traffic that network will support and the possible interference level depending on the number of interference sources. The tool can also be used by the device manufacturer to compare/select chipsets, batteries or alternatively optimize the some parameters of the communication protocols for a selected hardware to get the desired battery life. The model also provides insights to the major components that contributes to the power consumption under different number of operations and different traffic conditions. Finally the paper provides strategies to mitigate the effect of the different components contributing to the power consumption.
AbstractList Battery life of low power devices is a major concern for the users of such devices. Existing research focuses on using different power management techniques and power consumption models to predict the battery life. However most of the exiting power consumption models and simulators assume a high degree of technical expertise of the users such as user of a home automation system. This paper proposes a power consumption model that can be used as an easy to use engineering tool by the end user or system integrators to estimate the battery life of the device by just estimating the levels related to expected traffic that network will support and the possible interference level depending on the number of interference sources. The tool can also be used by the device manufacturer to compare/select chipsets, batteries or alternatively optimize the some parameters of the communication protocols for a selected hardware to get the desired battery life. The model also provides insights to the major components that contributes to the power consumption under different number of operations and different traffic conditions. Finally the paper provides strategies to mitigate the effect of the different components contributing to the power consumption. 
Battery life of low power devices is a major concern for the users of such devices. Existing research focuses on using different power management techniques and power consumption models to predict the battery life. However most of the exiting power consumption models and simulators assume a high degree of technical expertise of the users such as user of a home automation system. This paper proposes a power consumption model that can be used as an easy to use engineering tool by the end user or system integrators to estimate the battery life of the device by just estimating the levels related to expected traffic that network will support and the possible interference level depending on the number of interference sources. The tool can also be used by the device manufacturer to compare/select chipsets, batteries or alternatively optimize the some parameters of the communication protocols for a selected hardware to get the desired battery life. The model also provides insights to the major components that contributes to the power consumption under different number of operations and different traffic conditions. Finally the paper provides strategies to mitigate the effect of the different components contributing to the power consumption.
Author Zhu, Shaoling
Min, Xiaoyu
Pang, Zhibo
Bag, Gargi
Johansson, Morgan E.
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Keywords Wireless sensor network
Battery life
Internet of Things
Power consumption model
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SubjectTerms Battery life
Internet of Things
Power consumption model
Wireless sensor network
Title Engineering friendly tool to estimate battery life of a wireless sensor node
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