Energy-Aware Fault Tolerant Task offloading of Mobile Cloud Computing

Sura Khalil Abd, S. Al-Haddad, F. Hashim, Azizol Abdullah, S. Yussof
{"title":"Energy-Aware Fault Tolerant Task offloading of Mobile Cloud Computing","authors":"Sura Khalil Abd, S. Al-Haddad, F. Hashim, Azizol Abdullah, S. Yussof","doi":"10.1109/MobileCloud.2017.26","DOIUrl":null,"url":null,"abstract":"With all the hardware advances that have beenachieved lately relating to hand-held mobile devices, stillresource-intensive applications consider an important issue. Theheavy computational tasks of these applications cannot beprocessed in the mobile device itself because of their limitedprocessing and storage capabilities. Recently, many attemptshave been achieved to handle this issue. Most of these attemptsare depending on utilizing remote servers of the cloudenvironment. This process which takes advantageous of cloudservices allows mobile users offloading their computationallycomplicated tasks to be processed in remote servers of cloudenvironment, giving the birth to what is called mobile cloudcomputing model. Despite the benefits that outcome from taskoffloading process, challenges of energy efficiency (e.g. energyconsumption for task processing), reliability (e.g. node failure),and time management (e.g. task deadline and execution time) stillneed to be significantly addressed. In this paper, we propose anovel scheduling technique based on DNA combinations andgenetic algorithm processing under the precedence level. Thistechnique is suggested to decrease the ratio of energyconsumption, minimize the processing time of the task executionwithout exceeding the task deadline, and provide reliability byretrieving the processed data successfully by the mobile deviceuser and avoid task failure in mobile cloud computing model.","PeriodicalId":106143,"journal":{"name":"2017 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MobileCloud.2017.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25

Abstract

With all the hardware advances that have beenachieved lately relating to hand-held mobile devices, stillresource-intensive applications consider an important issue. Theheavy computational tasks of these applications cannot beprocessed in the mobile device itself because of their limitedprocessing and storage capabilities. Recently, many attemptshave been achieved to handle this issue. Most of these attemptsare depending on utilizing remote servers of the cloudenvironment. This process which takes advantageous of cloudservices allows mobile users offloading their computationallycomplicated tasks to be processed in remote servers of cloudenvironment, giving the birth to what is called mobile cloudcomputing model. Despite the benefits that outcome from taskoffloading process, challenges of energy efficiency (e.g. energyconsumption for task processing), reliability (e.g. node failure),and time management (e.g. task deadline and execution time) stillneed to be significantly addressed. In this paper, we propose anovel scheduling technique based on DNA combinations andgenetic algorithm processing under the precedence level. Thistechnique is suggested to decrease the ratio of energyconsumption, minimize the processing time of the task executionwithout exceeding the task deadline, and provide reliability byretrieving the processed data successfully by the mobile deviceuser and avoid task failure in mobile cloud computing model.
移动云计算的能量感知容错任务卸载
随着最近与手持移动设备相关的所有硬件进步,仍然需要考虑资源密集型应用程序的一个重要问题。由于移动设备本身的处理和存储能力有限,这些应用程序的繁重计算任务无法在移动设备中处理。最近,许多尝试已经取得了解决这个问题。这些尝试中的大多数都依赖于利用云环境的远程服务器。这个过程利用了云服务的优势,允许移动用户将其计算复杂的任务卸载到云环境的远程服务器上处理,从而诞生了所谓的移动云计算模型。尽管任务卸载过程带来了好处,但能效(例如任务处理的能耗)、可靠性(例如节点故障)和时间管理(例如任务截止日期和执行时间)方面的挑战仍然需要得到显著解决。本文提出了一种基于DNA组合和遗传算法处理的优先级调度技术。在移动云计算模型中,建议采用该技术降低能耗比,在不超过任务期限的情况下最小化任务执行的处理时间,并通过移动设备用户成功检索处理过的数据来提供可靠性,避免任务失败。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信