A Comprehensive Survey on Load and Resources Management Techniques in the Homogeneous and Heterogeneous Cloud Environment

• Published in: Journal of physics. Conference series Vol. 1979; no. 1; pp. 12036 - 12062
• Main Authors: Kaur, Ramanpreet, Verma, Sahil, Kavita, Jhanjhi, NZ, Talib, M N
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.08.2021
• Subjects: Algorithms; Cloud; Cloud computing; Energy efficiency; Interoperability; Load balancing; Multi-cloud; Optimization; Optimization techniques; Reliability analysis; Resource allocation; Resource management; Resource scheduling; Resources Allocation; Taxonomy
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1979/1/012036

Abstract Resource scheduling is a challenging job in multi-cloud environments. The multi-cloud technology attracted much research to work on it and look forward to solving the problems of vendors lock-in, reliability, interoperability, etc. The uncertainty in the multi-cloud environments with heterogeneous user demands made it a challenging job to dispense the resources on demand of the user. Researchers still focused on predicting efficient optimized resource allocation management from the existing resource allocation policies in multi-cloud environments. The research aims to provide a broad systematic literature analysis of resource management in the area of multi-cloud environments. The numbers of optimization techniques have been discussed among the open issues and future challenges in consideration due to flexibility and reliability in present environments. To analyses the literature work, it is necessary to cover the existing homogenous/heterogeneous user demands and cloud applications, and algorithms to manage it in multi-clouds. In this paper, we present the definition and classification of resource allocation techniques in multi-clouds and generalized taxonomy for resource management in cloud environments. In the last, we explore the open challenges and future directions of resource management in a multi-cloud environment.