Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/436
DC FieldValueLanguage
dc.contributor.authorChan, Anthony Hing Hungen_US
dc.contributor.otherBhamare, D.-
dc.contributor.otherSamaka, M.-
dc.contributor.otherErbad, A.-
dc.contributor.otherJain, R.-
dc.contributor.otherGupta, L.-
dc.date.accessioned2021-03-27T08:12:15Z-
dc.date.available2021-03-27T08:12:15Z-
dc.date.issued2017-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/436-
dc.description.abstractLately application service providers (ASPs) and Internet service providers (ISPs) are being confronted with the unprecedented challenge of accommodating increasing service and traffic demands from their geographically distributed users. Many ASPs and ISPs, such as Facebook, Netflix, AT&T and others have adopted micro service architecture to tackle this problem. Instead of building a single, monolithic application, the idea is to split the application into a set of smaller, interconnected services, called micro-services (or simply services). Such services are lightweight and perform distinct tasks independent of each other. Hence, they can be deployed quickly and independently as user demands vary. Nevertheless, scheduling of micro-services is a complex task and is currently under-researched. In this work, we address the problem of scheduling micro-services across multiple clouds, including micro-clouds. We consider different user-level SLAs, such as latency and cost, while scheduling such services. Our aim is to reduce overall turnaround time for the complete end-to-end service in service function chains and reduce the total traffic generated. In this work we present a novel fair weighted affinity-based scheduling heuristic to solve this problem. We also compare the results of proposed solution with standard biased greedy scheduling algorithms presented in the literature and observe significant improvements.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.titleMulti-objective scheduling of micro-services for optimal service function chainsen_US
dc.typeconference proceedingsen_US
dc.relation.publicationProceedings of the 2017 IEEE International Conference on Communications (ICC)-
dc.identifier.doi10.1109/ICC.2017.7996729-
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
dc.relation.isbn9781467390002-
dc.cihe.affiliatedNo-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairetypeconference proceedings-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.orcid0000-0001-7479-0787-
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