Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/82193
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dc.contributorDepartment of Computing-
dc.creatorLi, GS-
dc.creatorYao, YH-
dc.creatorWu, JH-
dc.creatorLiu, XX-
dc.creatorSheng, XF-
dc.creatorLin, QY-
dc.date.accessioned2020-05-05T05:59:02Z-
dc.date.available2020-05-05T05:59:02Z-
dc.identifier.issn1687-1472-
dc.identifier.urihttp://hdl.handle.net/10397/82193-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.en_US
dc.rightsThe following publication Li, G., Yao, Y., Wu, J. et al. A new load balancing strategy by task allocation in edge computing based on intermediary nodes. J Wireless Com Network 2020, 3, 1-10 (2020) is available at https://dx.doi.org/10.1186/s13638-019-1624-9en_US
dc.subjectEdge computingen_US
dc.subjectLoad balancingen_US
dc.subjectTask allocationen_US
dc.subjectState assessmenten_US
dc.titleA new load balancing strategy by task allocation in edge computing based on intermediary nodesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1-
dc.identifier.epage10-
dc.identifier.volume2020-
dc.identifier.issue1-
dc.identifier.doi10.1186/s13638-019-1624-9-
dcterms.abstractThe latency of cloud computing is high for the reason that it is far from terminal users. Edge computing can transfer computing from the center to the network edge. However, the problem of load balancing among different edge nodes still needs to be solved. In this paper, we propose a load balancing strategy by task allocation in edge computing based on intermediary nodes. The intermediary node is used to monitor the global information to obtain the real-time attributes of the edge nodes and complete the classification evaluation. First, edge nodes can be classified to three categories (light-load, normal-load, and heavy-load), according to their inherent attributes and real-time attributes. Then, we propose a task assignment model and allocate new tasks to the relatively lightest load node. Experiments show that our method can balance load among edge nodes and reduce the completion time of tasks.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEURASIP journal on wireless communications and networking, 2 Jan. 2020, v. 2020, no. 1, 3, p. 1-10-
dcterms.isPartOfEURASIP journal on wireless communications and networking-
dcterms.issued2020-
dc.identifier.isiWOS:000512694900002-
dc.identifier.scopus2-s2.0-85077309026-
dc.identifier.eissn1687-1499-
dc.identifier.artn3-
dc.description.validate202006 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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