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Cost Performance Driven Service Mashup: A Developer Perspective
Zhejiang University, Hangzhou, China.
Zhejiang University, Hangzhou, China.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science.ORCID iD: 0000-0001-9194-010X
The University of Sydney, Sydney, Australia.
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2015 (English)In: IEEE Transactions on Parallel and Distributed Systems, ISSN 1045-9219, E-ISSN 1558-2183, Vol. 27, no 8, 2234-2247 p.Article in journal (Refereed) 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.

Place, publisher, year, edition, pages
IEEE Press, 2015. Vol. 27, no 8, 2234-2247 p.
Keyword [en]
Cost Performance, Mashup Deployment, Service Composition, Service Mashup, Service Selection
National Category
Computer Systems
Research subject
Computer Science
URN: urn:nbn:se:kau:diva-40980DOI: 10.1109/TPDS.2015.2482980ISI: 000380060500006OAI: diva2:909507
Available from: 2016-03-07 Created: 2016-03-07 Last updated: 2016-10-14Bibliographically approved

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Taheri, Javid
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