Selection and Composition of Cloud Smart Services Using Trust Semantic-Based Green Quality Approach
Abstract
Nowadays, the massive use of new heterogeneous mobile devices and technologies for discovering, selecting and composing cloud smart services has led a trade-off between costs and improved quality of services (e.g., fast response time, low cost, improved security, the reduction of energy consumption, and considerable emissions of carbon). This trade-off has led most cloud service providers to call for new intelligent, faster, and energy-saving services selection and composition solutions. In order to make the cloud computing more attractive by the smart application, it is compulsory to provide best services that users can be satisfied once using them. This paper aims to propose a new generic green cloud service context-aware ontology to manage a large number of heterogeneous cloud services that are grouped semantically according to their service category, functional, and QoS descriptions. We propose also dynamic trust semantic-based bio-inspired selection algorithm that fits user's functional needs and QoS preferences. It focuses on composition process adaptation to context changes (evolution of user's needs and their preferences, energy saving and its execution environment). Also, our approach targets to determine optimal composite service from several relevant cloud smart services results from the selection phase in order to respect the users' global user's needs, energy saving, and quality services' experiences.