Priority-Based and Optimized Data Center Selection in Cloud Computing

  • Najib A. KofahiEmail author
  • Tariq Alsmadi
  • Malek Barhoush
  • Moy’awiah A. Al-Shannaq
Research Article - Computer Engineering and Computer Science


Cloud computing (CC) is rapidly emerging in IT fields and becomes a vital research area. CC environment allows cloud service providers to offer different types of services to customers of different categories. Customers like their requests to be processed at the lowest cost and minimum response time, which is highly dependent on the receiving datacenter (DC). Selecting a DC is entitled to the service broker that operates in accordance with a built-in routing policy. Improper selection of a DC may cause a bottleneck in the service brokerage architecture, resulting in resource bleeding (time and money). Moreover, cloud services are charged based on a pay-per-use model. Therefore, this paper proposes an efficient service broker routing policy that improves users’ satisfaction and cloud performance. The proposed policy employs the Vector Space Model and a multi-objective scalarization function to optimize conflicting objectives. The simulation-based approach was used to test the performance of the proposed methodology. The results show the ability of the proposed methodology to improve DC selection process based on the user’s priorities. Moreover, the performance of the proposed methodology has been compared with related works; the results show a significant improvement in average DC processing time, response time and total cost.


Cloud computing Data center selection Service broker Cloud simulation Multi-objective optimization Vector space mode 


Author Contributions

NK & TA contributed to an intensive literature review for very important and recent work in the field. NK & TA defines baselines and important factors that should be considered in the service broker routing policy. NK, TA & MB proposes an efficient and dynamic service broker policy by handling the DC selection problem as a multi-objective problem, where conflicting objectives might exist. For example, a DC may exist that has the lowest cost but not the most capable, while there exists another DC that has a slightly higher cost but way more capable than the lowest cost DC. Hence, selecting the later DC would be a wise decision to be considered by the service broker routing policy. Moreover, considering the fact that the service broker should select DCs as soon as possible with no possible delays, it is preferred to preset the user’s requirements before initialization and at runtime the service broker should be able to select the appropriate DCs without user’s intervention. Therefore, by considering the requirements and needs of the problem being researched, we propose a solution by handling the DC selection problem as a multi-objective and non-interactive problem through employing heuristic test jobs and Vector Space Model and scalarization function for multi-objective optimization. MAA recommends future work and further research approaches. NK, TA, MB & MAA performed formatting and language proofing.


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Copyright information

© King Fahd University of Petroleum & Minerals 2019

Authors and Affiliations

  1. 1.Yarmouk UniversityIrbidJordan

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