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.