Energy optimal wireless data transmission for wearable devices : a compression approach

Wearable devices are designed to have a small size and be lightweight. Consequently, the battery life is constrained and becomes a crucial limitation. In this paper, we use both data compression and wireless transmission speed control to minimize the energy consumption of wearable devices for data t...

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Main Authors: Zhang, Wei, Fan, Rui, Wen, Yonggang, Liu, Fang
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/142718
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1427182020-06-29T02:51:56Z Energy optimal wireless data transmission for wearable devices : a compression approach Zhang, Wei Fan, Rui Wen, Yonggang Liu, Fang School of Computer Science and Engineering Engineering::Computer science and engineering Compression Energy Wearable devices are designed to have a small size and be lightweight. Consequently, the battery life is constrained and becomes a crucial limitation. In this paper, we use both data compression and wireless transmission speed control to minimize the energy consumption of wearable devices for data transmission, subject to a deadline constraint. We consider both an off-line setting where future channel gains are known ahead of time and a stochastic setting where channel gains change stochastically according to a Markov process. For the first case, we present an efficient (1+ϵ) approximation algorithm for an arbitrarily small ϵ, while in the latter case we give a stochastic algorithm to minimize the total expected energy use. We also conduct experimental studies on the proposed algorithms and show that the stochastic algorithm, despite not knowing future channel gains, closely approximates the performance of the nearly optimal off-line solution with less than 0.1% difference in energy consumption on an average. We also compared the stochastic algorithm with several other practical algorithms and showed that our algorithm achieves significant improvements in the overall energy use. NRF (Natl Research Foundation, S’pore) 2020-06-29T02:51:56Z 2020-06-29T02:51:56Z 2018 Journal Article Zhang, W., Fan, R., Wen, Y., & Liu, F. (2018). Energy optimal wireless data transmission for wearable devices : a compression approach. IEEE Transactions on Vehicular Technology, 67(10), 9605 - 9618. doi:10.1109/TVT.2018.2859433 0018-9545 https://hdl.handle.net/10356/142718 10.1109/TVT.2018.2859433 2-s2.0-85050620820 10 67 9605 9618 en IEEE Transactions on Vehicular Technology © 2018 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Compression
Energy
spellingShingle Engineering::Computer science and engineering
Compression
Energy
Zhang, Wei
Fan, Rui
Wen, Yonggang
Liu, Fang
Energy optimal wireless data transmission for wearable devices : a compression approach
description Wearable devices are designed to have a small size and be lightweight. Consequently, the battery life is constrained and becomes a crucial limitation. In this paper, we use both data compression and wireless transmission speed control to minimize the energy consumption of wearable devices for data transmission, subject to a deadline constraint. We consider both an off-line setting where future channel gains are known ahead of time and a stochastic setting where channel gains change stochastically according to a Markov process. For the first case, we present an efficient (1+ϵ) approximation algorithm for an arbitrarily small ϵ, while in the latter case we give a stochastic algorithm to minimize the total expected energy use. We also conduct experimental studies on the proposed algorithms and show that the stochastic algorithm, despite not knowing future channel gains, closely approximates the performance of the nearly optimal off-line solution with less than 0.1% difference in energy consumption on an average. We also compared the stochastic algorithm with several other practical algorithms and showed that our algorithm achieves significant improvements in the overall energy use.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Zhang, Wei
Fan, Rui
Wen, Yonggang
Liu, Fang
format Article
author Zhang, Wei
Fan, Rui
Wen, Yonggang
Liu, Fang
author_sort Zhang, Wei
title Energy optimal wireless data transmission for wearable devices : a compression approach
title_short Energy optimal wireless data transmission for wearable devices : a compression approach
title_full Energy optimal wireless data transmission for wearable devices : a compression approach
title_fullStr Energy optimal wireless data transmission for wearable devices : a compression approach
title_full_unstemmed Energy optimal wireless data transmission for wearable devices : a compression approach
title_sort energy optimal wireless data transmission for wearable devices : a compression approach
publishDate 2020
url https://hdl.handle.net/10356/142718
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