Abstract
Cloud providers shares their resources and services through collaboration in order to increase resource utilization, profit and quality of services. The offered services with different access patterns, similar characteristics, varied performance levels and cost models create a heterogeneous service environment. It becomes a challenging task for users to decide a suitable service as per their application requirements. Cloud broker, an inter-mediator is required in service management to help both cloud providers and users. Cloud broker has to store all the information related to services and feedback of users on those services in order to provide the best services to end-users. Brokering model for service selection (BSS) has been proposed which employs integrated weighting approach in cloud service selection. Subjective and objective weights of QoS attributes are combined to compute integrated total weight. Subjective weight is obtained from users’ feedback on QoS attributes of a cloud service while objective weight is computed from benchmark tested data of cloud services. Users’ feedback and preferences given to QoS parameters are employed in subjective weight computation. Objective weight is computed using Shannon’s Entropy method. Total weight is obtained by combining subjective and objective weights. BSS method is employed to rank cloud services. Simulation with a case study on real dataset has been done to validate the effectiveness of BSS. The obtained results demonstrate the consistency of model for handling rank reversal problem and provides better execution time than other state-of-the art solutions.
Highlights
Cloud Computing delivers computing services such as storage, networking, processing, etc. on demand and subscription basis over Internet. These services are offered as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) [1]
We have proposed a brokering model for service selection in cloud environment which employs integrated weighting approach named as Brokering model for service selection (BSS)
Service selection has been done by employing integrated weighting approach
Summary
Cloud Computing delivers computing services such as storage, networking, processing, etc. on demand and subscription basis over Internet. BSS collects end users’ feedback on various QoS attributes, converts into crisp numerical value and employs it for service evaluation Kumar et al [35] have proposed a framework for selection of cloud services considering fuzzy environment Users can provide their input for QoS parameters through linguistic terms. This may lead to false decision in service selection Users provide their subjective assessment about a QoS parameter of a cloud service which is generally in linguistic term such as high, good, bad [43]. User provides an preference to a QoS attributes of a cloud service such as high reliable cloud service This preference is converted into a weight value in computation.
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