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In cloud computing domain, often service providers offer services with same functionalities, but with varying quality metrics. A suitable service selection method finds the most appropriate solution among the alternatives. The challenge is to deliver a solution satisfying the requirement (quality and other) of a consumer with minimum possible execution time. Many conflicting QoS objectives increase the complexity of the problem. In fact, the problem may be formulated as a multi-objective, NP-hard optimization problem. Most of the existing solutions either satisfies the QoS demands of consumer or only reduces execution time by considering a sub-set of required QoS metrics. Consumer’s feedback on the choice of required QoS metrics not only shall help increasing user satisfaction, but also may reduce the complexity effectively. However, this depends on the domain knowledge of a consumer. In this work, we have proposed a goodness measure that replaces all QoS metrics by a single one. The new technique using dimension reduction is proposed to offer significant improvement compared to the existing works in terms of execution time. Moreover, the solution satisfies all the QoS requirements of a consumer in most of the cases. The proposed data driven selection approach has been implemented and the experimental results substantiate the claims as mentioned. |
