2 research outputs found

    Multi-Criteria Service Selection Agent for Federated Cloud

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    Federated cloud interconnects small and medium-sized cloud service providers for service enhancement to meet demand spikes. The service bartering technique in the federated cloud enables service providers to exchange their services. Selecting an optimal service provider to share services is challenging in the cloud federation. Agent-based and Reciprocal Resource Fairness (RRF) based models are used in the federated cloud for service selection. The agent-based model selects the best service provider using Quality of Service (quality of service). RRF model chooses fair service providers based on service providers\u27 previous service contribution to the federation. However, the models mentioned above fail to address free rider and poor performer problems during the service provider selection process. To solve the above issue, we propose a Multi-criteria Service Selection (MCSS) algorithm for effectively selecting a service provider using quality of service, Performance-Cost Ratio (PCR), and RRF. Comprehensive case studies are conducted to prove the effectiveness of the proposed algorithm. Extensive simulation experiments are conducted to compare the proposed algorithm performance with the existing algorithm. The evaluation results demonstrated that MCSS provides 10% more services selection efficiency than Cloud Resource Bartering System (CRBS) and provides 16% more service selection efficiency than RPF

    A reputation-based approach to improve QoS in cloud service composition

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    Cloud Computing is a versatile computing paradigm capable of attracting a wide variety of applications. However, the necessity to provide a wide range of complex services led providers to establish mutual agreements to provide large-scale distributed multi-cloud environments. Providers gain the opportunity to compose service workflows that are effective and efficient, taking resources of their own competitors, and the capability to satisfy unexpected workload peaks. In this paper, we propose a reputation-based model aiming at supporting the service composition by considering measures of QoS collected by the measuring systems, and reputation measures collected with the customers by means of users feedback
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