A SURVEY OF RESOURCE MANAGEMENT CHALLENGES IN MULTI-CLOUD ENVIRONMENT: TAXONOMY AND EMPIRICAL ANALYSIS
Journal Title: Azerbaijan Journal of High Performance Computing - Year 2018, Vol 1, Issue 1
Abstract
HOME ABOUT SUBMISSION SEARCH CURRENT ARCHIVES A SURVEY OF RESOURCE MANAGEMENT CHALLENGES IN MULTI-CLOUD ENVIRONMENT: TAXONOMY AND EMPIRICAL ANALYSIS Hits: 159 PDF Volume 1 (1), July 2018, Pages 51-65 Bandar Aldawsari1, Thar Baker1, Muhammad Asim2, Zakaria Maamar3, Dhiya Al-Jumeily1, Mohammed Alkhafajiy1 1 Department of Computer Science, Liverpool John Moores University, Liverpool, UK B.M.Aldawsari@2012.ljmu.ac.uk; t.baker@ljmu.ac.uk; D.aljumeily@ljmu.ac.uk; M.D.Alkhafajiy@2016.ljmu.ac.uk 2 Department of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Pakistan, muhammad.asim@nu.edu.pk 3 College of Technological Innovation, Zayed University, Abu Dhabi, UAE, Zakaria.Maamar@zu.ac.ae 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.
Authors and Affiliations
Bandar Aldawsari, Thar Baker, Muhammad Asim, Dhiya Al-Jumeily, Mohammed Alkhafajiy, Zakaria Maamar
Keywords
Related Articles
- EP ID EP523611
- DOI 10.32010/26166127.2018.1.1.51.65
- Views 71
- Downloads 0
EXAMIG MATRIX: PROCESS MIGRATION BASED ON MATRIX DEFINITION OF SELECTING DESTINATION IN DISTRIBUTED EXASCALE ENVIRONMENTS
In traditional computing system, load balancer, interim selecting the process, determine the destination computing node based on describing Indicators process status. In distributed Exascale computing system, due to the...
CONVERGENCE OF HPC AND AI: TWO DIRECTIONS OF CONNECTION PDF
This paper examines the role of HPC systems in the solution of the most AI problems, on the other hand, assesses the impact of the application of AI methods on the resolution of different tasks in distributed systems. Th...
CHALLENGES OF RESOURCE DISCOVERY TO SUPPORT DISTRIBUTED EXASCALE COMPUTING ENVIRONMENT
The resource discovery management unit (RD) in distributed Exascale systems needs to be able to manage the occurrence of dynamic and interactive events in the requesting process when running activities related to RD. The...
ISE: AN INTELLIGENT AND EFFICIENT STEGANALYSIS ENGINE FOR IMAGE DATABASE IN BIG DATA SYSTEMS
The aim of this work is to design a faster and artificially intelligent steganalysis engine, which is able to secure the image databases from any infected image in big data environment. The proposed Intelligent Steganaly...
CONTROLLING OPTIMIZATION SOFTWARE PACKAGES WITH THE APPLICATION OF PARALLEL COMPUTING
The paper is devoted to the analysis of techniques and algorithms of controlling computational process of solution to complex optimization problems with the use of multiprocessor and/or multicore computer systems. We hav...