Towards a Constraint-based Approach for Service Aggregation and Selection in Cloud E-Marketplaces
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Abstract
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Service providers leverage cloud ecosystems and cloud e-marketplaces to increase the business value of their
services to reach a wider range of service users. The operations of commercial e-marketplaces can be further enhanced by enabling service composition mechanisms that allow automatic aggregation of atomic services into composite offerings that meets complex user requirements. Existing approaches of cloud service selection are yet to achieve this. Currently, users are constrained to make choices only from a set of predefined atomic services, or at best, manually configure their desirable features and QoS requirements in order to realize their complex requirements given that they have deep knowledge of the service domain. In this paper, a constraint-based approach for service
composition and selection to address this problem was proposed. The proposed approach applies constraint-based automated reasoning on feature models to formally guide the aggregation of atomic services to offer composite services in order to satisfy complex requirements with minimal user involvement. The plausibility of the proposed approach is demonstrated via an illustrative customer relationship management (CRM) service ecosystem. The study offers a credible way to replicate the kind of user experience that is currently available on e-commerce platforms in cloud service e-marketplaces.
Keywords
Q Science (General), QA75 Electronic computers. Computer science, QA76 Computer software