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research-article

Multi-device task offloading with time-constraints for energy efficiency in mobile cloud computing

Authors:

Xiaoyong Zhang,

Weirong LiuAuthors Info & Claims

Future Generation Computer Systems, Volume 64, Issue C

Pages 1 - 14

https://doi.org/10.1016/j.future.2016.04.013

Published: 01 November 2016 Publication History

Abstract

Nowadays, in order to deal with the increasingly complex applications on mobile devices, mobile cloud offloading techniques have been studied extensively to meet the ever-increasing energy requirements. In this study, an offloading decision method is investigated to minimize the energy consumption of mobile device with an acceptable time delay and communication quality. In general, mobile devices can execute a sequence of tasks in parallel. In the proposed offloading decision method, only parts of the tasks are offloaded for task characteristics to save the energy of multi-devices. The issue of the offloading decision is formulated as an NP-hard 0-1 nonlinear integer programming problem with time deadline and transmission error rate constraints. Through decision-variable relaxation from the integer to the real domain, this problem can be transformed as a continuous convex optimization. Based on Lagrange duality and the Karush-Kuhn-Tucker condition, a solution with coupled terms is derived to determine the priority of tasks for offloading. Then, an iterative decoupling algorithm with high efficiency is proposed to obtain near-optimal offloading decisions for energy saving. Simulation results demonstrate that considerable energy can be saved via the proposed method in various mobile cloud scenarios. A task offloading decision method is proposed among multi-devices for energy saving.The problem is formalized as a 0-1 nonlinear integer programming problem.An iterative decoupling algorithm that combines with decision-variable relaxation and convex optimization is proposed for near-optimal decisions.

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Cited By

Ben Sada AKhelloufi ANaouri ANing HDhelim S(2024)Hybrid metaheuristics for selective inference task offloading under time and energy constraints for real-time IoT sensing systemsCluster Computing10.1007/s10586-024-04578-127:9(12965-12981)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s10586-024-04578-1
Popli SJha RJain S(2022)Green IoT: A Short Survey on Technical Evolution & TechniquesWireless Personal Communications: An International Journal10.1007/s11277-021-09142-3123:1(525-553)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s11277-021-09142-3
Xu FZhang ZFeng JQin ZXie Y(2022)Efficient deployment of multi‐UAV assisted mobile edge computingTransactions on Emerging Telecommunications Technologies10.1002/ett.445333:5Online publication date: 27-May-2022
https://dl.acm.org/doi/10.1002/ett.4453
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Multi-device task offloading with time-constraints for energy efficiency in mobile cloud computing
1. General and reference
  1. Cross-computing tools and techniques
2. Networks
  1. Network types

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Published In

cover image Future Generation Computer Systems

Future Generation Computer Systems Volume 64, Issue C

November 2016

229 pages

ISSN:0167-739X

Issue’s Table of Contents

Copyright © Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 November 2016

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Cited By

Ben Sada AKhelloufi ANaouri ANing HDhelim S(2024)Hybrid metaheuristics for selective inference task offloading under time and energy constraints for real-time IoT sensing systemsCluster Computing10.1007/s10586-024-04578-127:9(12965-12981)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s10586-024-04578-1
Popli SJha RJain S(2022)Green IoT: A Short Survey on Technical Evolution & TechniquesWireless Personal Communications: An International Journal10.1007/s11277-021-09142-3123:1(525-553)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s11277-021-09142-3
Xu FZhang ZFeng JQin ZXie Y(2022)Efficient deployment of multi‐UAV assisted mobile edge computingTransactions on Emerging Telecommunications Technologies10.1002/ett.445333:5Online publication date: 27-May-2022
https://dl.acm.org/doi/10.1002/ett.4453
Chanyour TEl Ghmary MHmimz YCherkaoui Malki M(2022)Energy‐efficient and delay‐aware multitask offloading for mobile edge computing networksTransactions on Emerging Telecommunications Technologies10.1002/ett.367333:3Online publication date: 21-Mar-2022
https://dl.acm.org/doi/10.1002/ett.3673
Danial CSaroit IMohamed S(2020)Energy Efficient Ant Colony Cloud Offloading Algorithm (EACO)Proceedings of the 9th International Conference on Software and Information Engineering10.1145/3436829.3436846(190-197)Online publication date: 11-Nov-2020
https://dl.acm.org/doi/10.1145/3436829.3436846
Abraham SAl-Khatib OAbdul Malek M(2020)Energy-efficient and delay-aware mobile cloud offloading over cellular networksTelecommunications Systems10.1007/s11235-019-00585-573:1(131-142)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1007/s11235-019-00585-5
Guan SBoukerche ADe Rango FCalafate CVoznak M(2019)A MEC-based distributed offloading model for ubiquitous and time-constraint offloadingProceedings of the 23rd IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications10.5555/3395101.3395106(25-32)Online publication date: 7-Oct-2019
https://dl.acm.org/doi/10.5555/3395101.3395106
Boukerche AGuan SGrande R(2019)Sustainable Offloading in Mobile Cloud ComputingACM Computing Surveys10.1145/328668852:1(1-37)Online publication date: 21-Feb-2019
https://dl.acm.org/doi/10.1145/3286688
Kim YLee HChong S(2019)Mobile Computation Offloading for Application Throughput Fairness and Energy EfficiencyIEEE Transactions on Wireless Communications10.1109/TWC.2018.286867918:1(3-19)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1109/TWC.2018.2868679
Salehan ADeldari HAbrishami S(2019)An online context-aware mechanism for computation offloading in ubiquitous and mobile cloud environmentsThe Journal of Supercomputing10.1007/s11227-019-02743-775:7(3769-3809)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11227-019-02743-7
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