۱- Introduction

۲- Related work

۳- Problem formulation

۴- Experiments and results

۵- Conclusions

References

Abstract

Cloud computing refers to providing computing services and resources over the Internet. The cloud provider is an organization or company which offers the services to the consumer at different levels of features and characteristics. However, as the growth of cloud services as well as cloud service providers are increasing rapidly, it is becoming a challenge for consumers to choose the best service provider based on their requirements. In this paper, we propose a method to help the consumer to answer this question. A hybrid multi criteria decision method (MCDM) is developed to evaluate and rank cloud service providers from Smart data. Furthermore, this method considers the interdependencies and relations between the performance measurements. The hybrid method consists of two components: (i) clustering the providers using k-means algorithm to consolidate cloud service providers with similar features and (ii) applying MCDM methods using DEMATEL-ANP to rank clusters and make a final decision. The proposed method also considers the existing workloads of the organization as well as assigns different importance and weights for a set of criteria by clustering the cloud service providers using k-means algorithm. A simulation on the MATLAB was performed to evaluate the proposed method, and the results indicate how the proposed hybrid approach can provide an accurate and efficient way to select the best providers.

Introduction

Cloud computing is emerging technology in computing resources allocation over the Internet. This model of computing provides important benefits to the organizations by relieving them of low-level tasks related to setting up IT infrastructure as well as allowing organizations to begin small resources and increase these resources on demand, thus enabling more time for innovation and the creation of business value. This technology is a model for providing a pool of on demand resources like software as a service SaaS, infrastructure as a service IaaS, and platform as a service PaaS [1]. Nowadays, migrating the applications, data, and/or infrastructure to a cloud is a confirmed challenging process. Certain obstacles prevent cloud computing from offering its full features. Those obstacles are related to the fact that current applications, data, and/or infrastructure have specific needs and configurations that must be realized by the cloud provider [1, 2]. From an organization’s perspective, each system has its own configuration performance and factors that affect workload parameters. Furthermore, each cloud service provider offers its services with various features such as performance, cost, and security. Therefore, it is challenging for organizations to choose the most appropriate cloud service provider in the presence of these multiple features.