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A Survey of Resource Management Challenges in Multi-cloud Environment: Taxonomy and Empirical Analysis

Aldawsari, B, Baker, T, Asim, M, Maamar, Z, Al-Jumeily, D and Alkhafajiy, M (2018) A Survey of Resource Management Challenges in Multi-cloud Environment: Taxonomy and Empirical Analysis. Azerbaijan Journal of High Performance Computing, 1 (1). pp. 51-56. ISSN 2616-6127

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Abstract

Cloud computing has seen a great deal of interest by researchers and industrial firms since its first coined. Different perspectives and research problems, such as energy efficiency, security and threats, to name but a few, have been dealt with and addressed from cloud computing perspective. However, cloud computing environment still encounters a major challenge of how to allocate and manage computational resources efficiently. Furthermore, due to the different architectures and cloud computing networks and models used (i.e., federated clouds, VM migrations, cloud brokerage), the complexity of resource management in the cloud has been increased dramatically. Cloud providers and service consumers have the cloud brokers working as the intermediaries between them, and the confusion among the cloud computing parties (consumers, brokers, data centres and service providers) on who is responsible for managing the request of cloud resources is a key issue. In a traditional scenario, upon renting the various cloud resources from the providers, the cloud brokers engage in subletting and managing these resources to the service consumers. However, providers’ usually deal with many brokers, and vice versa, and any dispute of any kind between the providers and the brokers will lead to service unavailability, in which the consumer is the only victim. Therefore, managing cloud resources and services still needs a lot of attention and effort. This paper expresses the survey on the systems of the cloud brokerage resource management issues in multi-cloud environments.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science
Publisher: AZJHPC
Date Deposited: 05 Sep 2018 11:32
Last Modified: 15 Sep 2018 04:24
DOI or Identification number: 10.32010/26166127.2018.1.1.51.65
URI: http://researchonline.ljmu.ac.uk/id/eprint/9171

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