Energy-efficient task execution for application as a general topology in mobile cloud computing

Mobile cloud computing has been proposed as an effective solution to augment the capabilities of resource-poor mobile devices. In this paper, we investigate energy-efficient collaborative task execution to reduce the energy consumption on mobile devices. We model a mobile application as a general to...

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Main Authors: Zhang, Weiwen, Wen, Yonggang
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/140150
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1401502020-05-27T02:38:53Z Energy-efficient task execution for application as a general topology in mobile cloud computing Zhang, Weiwen Wen, Yonggang School of Computer Science and Engineering Engineering::Computer science and engineering Mobile Cloud Computing Energy Efficiency Mobile cloud computing has been proposed as an effective solution to augment the capabilities of resource-poor mobile devices. In this paper, we investigate energy-efficient collaborative task execution to reduce the energy consumption on mobile devices. We model a mobile application as a general topology, consisting of a set of fine-grained tasks. Each task within the application can be either executed on the mobile device or on the cloud. We aim to find out the execution decision for each task to minimize the energy consumption on the mobile device while meeting a delay deadline. We formulate the collaborative task execution as a delay-constrained workflow scheduling problem. We leverage the partial critical path analysis for the workflow scheduling; for each path, we schedule the tasks using two algorithms based on different cases. For the special case without execution restriction, we adopt one-climb policy to obtain the solution. For the general case where there are some tasks that must be executed either on the mobile device or on the cloud, we adopt Lagrange Relaxation based Aggregated Cost (LARAC) algorithm to obtain the solution. We show by simulation that the collaborative task execution is more energy-efficient than local execution and remote execution. MOE (Min. of Education, S’pore) 2020-05-27T02:38:52Z 2020-05-27T02:38:52Z 2015 Journal Article Zhang, W., & Wen, Y. (2018). Energy-efficient task execution for application as a general topology in mobile cloud computing. IEEE Transactions on Cloud Computing, 6(3), 708-719. doi:10.1109/TCC.2015.2511727 2168-7161 https://hdl.handle.net/10356/140150 10.1109/TCC.2015.2511727 3 6 708 719 en IEEE Transactions on Cloud Computing © 2015 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Mobile Cloud Computing
Energy Efficiency
spellingShingle Engineering::Computer science and engineering
Mobile Cloud Computing
Energy Efficiency
Zhang, Weiwen
Wen, Yonggang
Energy-efficient task execution for application as a general topology in mobile cloud computing
description Mobile cloud computing has been proposed as an effective solution to augment the capabilities of resource-poor mobile devices. In this paper, we investigate energy-efficient collaborative task execution to reduce the energy consumption on mobile devices. We model a mobile application as a general topology, consisting of a set of fine-grained tasks. Each task within the application can be either executed on the mobile device or on the cloud. We aim to find out the execution decision for each task to minimize the energy consumption on the mobile device while meeting a delay deadline. We formulate the collaborative task execution as a delay-constrained workflow scheduling problem. We leverage the partial critical path analysis for the workflow scheduling; for each path, we schedule the tasks using two algorithms based on different cases. For the special case without execution restriction, we adopt one-climb policy to obtain the solution. For the general case where there are some tasks that must be executed either on the mobile device or on the cloud, we adopt Lagrange Relaxation based Aggregated Cost (LARAC) algorithm to obtain the solution. We show by simulation that the collaborative task execution is more energy-efficient than local execution and remote execution.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Zhang, Weiwen
Wen, Yonggang
format Article
author Zhang, Weiwen
Wen, Yonggang
author_sort Zhang, Weiwen
title Energy-efficient task execution for application as a general topology in mobile cloud computing
title_short Energy-efficient task execution for application as a general topology in mobile cloud computing
title_full Energy-efficient task execution for application as a general topology in mobile cloud computing
title_fullStr Energy-efficient task execution for application as a general topology in mobile cloud computing
title_full_unstemmed Energy-efficient task execution for application as a general topology in mobile cloud computing
title_sort energy-efficient task execution for application as a general topology in mobile cloud computing
publishDate 2020
url https://hdl.handle.net/10356/140150
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