Journal
ACM COMPUTING SURVEYS
Volume 48, Issue 3, Pages -Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2843889
Keywords
Documentation; Cloud Computing; Methodical Analysis; Theory; Management; Resource provisioning; cloud computing; autonomic management; service-level agreement; quality of service; grid computing; resource scheduling; autonomic cloud computing; autonomic computing; self-management; self-optimizing; self-protecting; self-healing; self-configuring; resource management
Categories
Funding
- Department of Science and Technology (DST), Government of India [201400000761 [DST/INSPIRE/03/2014/000359]]
- DST
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As computing infrastructure expands, resource management in a large, heterogeneous, and distributed environment becomes a challenging task. In a cloud environment, with uncertainty and dispersion of resources, one encounters problems of allocation of resources, which is caused by things such as heterogeneity, dynamism, and failures. Unfortunately, existing resource management techniques, frameworks, and mechanisms are insufficient to handle these environments, applications, and resource behaviors. To provide efficient performance of workloads and applications, the aforementioned characteristics should be addressed effectively. This research depicts a broad methodical literature analysis of autonomic resource management in the area of the cloud in general and QoS (Quality of Service)-aware autonomic resource management specifically. The current status of autonomic resource management in cloud computing is distributed into various categories. Methodical analysis of autonomic resource management in cloud computing and its techniques are described as developed by various industry and academic groups. Further, taxonomy of autonomic resource management in the cloud has been presented. This research work will help researchers find the important characteristics of autonomic resource management and will also help to select the most suitable technique for autonomic resource management in a specific application along with significant future research directions.
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