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Cost Performance Driven Service Mashup: A Developer Perspective
Zhejiang University, Hangzhou, China.
Zhejiang University, Hangzhou, China.
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap.ORCID-id: 0000-0001-9194-010X
The University of Sydney, Sydney, Australia.
Vise andre og tillknytning
2016 (engelsk)Inngår i: IEEE Transactions on Parallel and Distributed Systems, ISSN 1045-9219, E-ISSN 1558-2183, Vol. 27, nr 8, s. 2234-2247Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Service mashups are applications created by combining single-functional services (or APIs) dispersed over the web. With the development of cloud computing and web technologies, service mashups are becoming more and more widely used and a large number of mashup platforms have been produced. However, due to the proliferation of services on the web, how to select component services to create mashups has become a challenging issue. Most developers pay more attention to the QoS (quality of service) and cost of services. Beside service selection, mashup deployment is another pivotal process, as the platform can significantly affect the quality of mashups. In this paper, we focus on creating service mashups from the perspective of developers. A genetic algorithm-based method, GA4MC (genetic algorithm for mashup creation), is proposed to select component services and deployment platforms in order to create service mashups with optimal cost performance. A series of experiments are conducted to evaluate the performance of GA4MC. The results show that the GA4MC method can achieve mashups whose cost performance is extremely close to the optimal . Moreover, the execution time of GA4MC is in a low order of magnitude and the algorithm performs good scalability as the experimental scale increases.

sted, utgiver, år, opplag, sider
OS ALAMITOS, CA 90720-1314 USA: IEEE Computer Society, 2016. Vol. 27, nr 8, s. 2234-2247
Emneord [en]
Cost Performance, Mashup Deployment, Service Composition, Service Mashup, Service Selection
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-40980DOI: 10.1109/TPDS.2015.2482980ISI: 000380060500006OAI: oai:DiVA.org:kau-40980DiVA, id: diva2:909507
Tilgjengelig fra: 2016-03-07 Laget: 2016-03-07 Sist oppdatert: 2017-11-02bibliografisk kontrollert

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