Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81747
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dc.contributorDepartment of Computing-
dc.creatorLi, GS-
dc.creatorYan, JH-
dc.creatorChen, L-
dc.creatorWu, JH-
dc.creatorLin, QY-
dc.creatorZhang, Y-
dc.date.accessioned2020-02-10T12:28:58Z-
dc.date.available2020-02-10T12:28:58Z-
dc.identifier.issn2169-3536-
dc.identifier.urihttp://hdl.handle.net/10397/81747-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rightsThis work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/en_US
dc.rightsThe following publication G. Li, J. Yan, L. Chen, J. Wu, Q. Lin and Y. Zhang, "Energy Consumption Optimization With a Delay Threshold in Cloud-Fog Cooperation Computing," in IEEE Access, vol. 7, pp. 159688-159697, 2019 is available at https://dx.doi.org/10.1109/ACCESS.2019.2950443en_US
dc.subjectDelaysen_US
dc.subjectTask analysisen_US
dc.subjectCloud computingen_US
dc.subjectEnergy consumptionen_US
dc.subjectOptimizationen_US
dc.subjectEdge computingen_US
dc.subjectServersen_US
dc.subjectEnergy consumption optimizationen_US
dc.subjectFog computingen_US
dc.subjectTasks schedulingen_US
dc.titleEnergy consumption optimization with a delay threshold in cloud-fog cooperation computingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage159688-
dc.identifier.epage159697-
dc.identifier.volume7-
dc.identifier.doi10.1109/ACCESS.2019.2950443-
dcterms.abstractWith the rapid development of the Internet of Things (IoT), the number of mobile terminal devices is increasing. Massive data are generated by mobile terminal devices, resulting in high delay and high energy consumption. In most cases, however, a low delay means high energy consumption. To balance energy consumption and delay, we adopt a tradeoff strategy that can realize optimal energy consumption with a delay threshold in this paper. First, we introduce the role of the delay threshold in reducing delay. Then, we describe the delay and energy consumption of the mobile terminal layer, fog node layer and cloud server layer with queue theory. Nonlinear programming is used to solve the energy optimization problem by calculating the optimal workload of each layer. We design a cloud-fog cooperation scheduling algorithm to reduce energy consumption. A task offloading algorithm is also designed to complete tasks when their nodes leave. The experimental results show that the energy consumption is reduced by approximately 22, while the delay is 12.5 less than the first come first served (FCFS) approach.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE access, 30 Oct. 2019, v. 7, p. 159688-159697-
dcterms.isPartOfIEEE access-
dcterms.issued2019-
dc.identifier.isiWOS:000497167600069-
dc.description.validate202002 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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