A correlation-driven optimal service selection approach for virtual enterprise establishment

Wu, Quanwang; Zhu, Qingsheng; Mingqiang, Zhou

doi:10.1007/s10845-013-0751-0

Cited by 49 publications

(15 citation statements)

References 36 publications

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“…Canfora et al (2005) present a genetic algorithm based approach to enhance the efficiency. The genetic algorithm for optimal service A c c e p t e d M a n u s c r i p t composition problem is also improved or extended in some other works (Canfora et al, 2008;Ma and Zhang, 2008;Wu et al, 2012;Wu et al, 2013). Yu et al (2007) propose a combinatorial model and a graph model to represent this problem, respectively.…”

Section: Service Composition For Individual Invocationsmentioning

confidence: 99%

Broker-based SLA-aware composite service provisioning

Wu¹,

Zhu²,

Jian³

et al. 2014

Journal of Systems and Software

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Section: Service Composition For Individual Invocationsmentioning

confidence: 99%

Broker-based SLA-aware composite service provisioning

Wu¹,

Zhu²,

Jian³

et al. 2014

Journal of Systems and Software

Self Cite

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“…However, they did not present how these factors are computed and their aim is to obtain the composite service that best suits these context factors. Several studies have addressed the optimal service selection problem with correlations taken into consideration [28,29]. They have considered the effect of service packages on the cost and regarded them as correlations.…”

Section: Related Workmentioning

confidence: 99%

Cost Performance Driven Service Mashup: A Developer Perspective

Deng

Taheri

et al. 2016

IEEE Trans. Parallel Distrib. Syst.

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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.

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“…Guo et al (2011b) presented the formalized description for composable correlations in cloud manufacturing systems, and proposed the decision algorithms to estimate composable correlations between cloud services based on bipartite graph. Wu et al (2014) focused on business correlations, which were divided into quality and selection correlations, and presented an efficient approach for optimal services selection based on genetic algorithm. Yet they did not give out correlations-description model.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Service composition aims to build a new value-added service by using existing services to meet the demands of manufacturing tasks (Wu et al 2014). Taking use of virtualization technologies, manufacturing resources providers virtualize and encapsulate their manufacturing resources and capabilities into manufacturing cloud services (MCSs), and then publish them in the resources pool through the Internet (Leitão et al 2012;Tao et al 2011;Wang et al 2012;Morariu et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Correlation-aware QoS modeling and manufacturing cloud service composition

2015

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Recently, cloud manufacturing has attracted much attention from both academic and industry communities. Manufacturing cloud service composition and optimization is critical to the optimal resources allocation in cloud manufacturing. Since there are many manufacturing cloud services available with similar functions but different quality of service (QoS), and with potential quality correlations among them, such correlations must to be considered for manufacturing cloud service composition. In this paper, a correlation-aware manufacturing cloud service description model is presented to characterize the QoS dependence of an individual service on other related services. Based on such a model, a service correlation mapping model is proposed for getting correlation QoS values among services automatically. In addition, an effective approach for the correlation-aware optimal service selection is proposed based on a genetic algorithm. A case study indicates that services composition of higher quality can be obtained when such correlations are considered. And the effectiveness and efficiency of the proposed approach are demonstrated via simulation studies.

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A correlation-driven optimal service selection approach for virtual enterprise establishment

Cited by 49 publications

References 36 publications

Broker-based SLA-aware composite service provisioning

Broker-based SLA-aware composite service provisioning

Cost Performance Driven Service Mashup: A Developer Perspective

Correlation-aware QoS modeling and manufacturing cloud service composition

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