Abstract
Workflow management system, a technique that manages different types of processes/jobs gathered as a workflow, ensures that each task in the workflow is accomplished to proceed further. When the process happens between two parties, the client and the server, a binding agreement or contract is defined specifying the Quality of Service (QoS) metrics such as products/services to be delivered, the deadlines and the cost of services. The goal of QoS is to select the appropriate web services for the customers achieve their goals. The existing service applications pretend to be a self-contained unit of functionalities that requests and retrieve a qualified service using service oriented architecture. But they face difficulties in identifying the right quality of a service based on functionality. Hence the major factor in QoS specification is QoS modeling, which involves the task of identifying the factors suitable for a functional requirement. QoS-aware service composition significantly affects the quality of a composite service and hence enormous research has been performed in this area. However, existing methods are restricted to predefined workflows, which can sustain the limitations. The limitations include the lack of guarantee for the optimality on overall QoS, satisfaction of customers and the completeness of finding a composite service solution. The proposed approach uses an Aggregated Quantified Response time Matrix Formulation (ARMF) methodology. The ARMF predicts the unknown QoS values by implementing two algorithms, the Aggregated Quantified Matrix Formulation (AQMF) Technique and the Optimal Incremental Multi-Attributes property Filtering (OIMF). It provides the user-response matrix where every entry in the matrix depicts the QoS value of the service opted by the user. The experimental results show that the proposed approach largely outperforms the existing techniques in terms of quality and efficiency required for the customer services.
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