عنوان مقاله [English]
نویسنده [English]چکیده [English]
The growth of Information and Communication Technology (ICT) has significantly increased the number of automated web service. Web services are self-contained, modular, distributed, dynamic applications that can be described, published, located, or invoked over the network to create products, processes, and supply chains. Besides, cloud computing has provided unprecedented opportunities for hosting, developing, publishing and applying web services. SOA, or Service Oriented Architecture, allows businesses to use the information technology infrastructure or existed software component to address new needs of the business. To tackle with a business flow of business plan, we need different web services. Usually web services are different both in functional and non-functional (or quality of service) requirements. Functional requirement states what tasks will provide by a web serivice and non-functional requirement states how web services perform that task. Besides, an atomic (or isolated) web service is limited both in functional requirements and quality of service parameters. Hence, we are faced with many unique services provided with similar functionality and different Quality of Service (QoS) parameters. Therefore, we need an efficient service composition while providing necessary QoS and user constraints (known as Service Level Agreement). Nearly most of the existing literature in service composition deals with finding the optimal composition using QoS values announced by providers in composition process. However, when the services are physically deployed and invoked by service consumer (user observations), these parameters values may vary largely depending on different factors like network load, number of applications running in the server, topology changes in network. In this paper we present a Cloud Web Service Composition (CWSC) based on user observations. Our proposed solution considers users observation in composition process to overcome the problem of varying QoS parameters value in users-side. We demonstrate our proposed method on real dataset to show the efficacy of our proposal.