A Metaheuristic Resource Allocation Scheme in Cloud Computing
Cloud computing is a extensive distributed computing model that enables applications and services for enterprises and users to use computing as a service. In this paper, we consider genetic method of cloud computing model, here cloud tasks arrives based on genetic process and resources,
which are specified as virtualized entities like virtual machine (VMs) are central process unit, internal memory and storage location. Cloud system consists of many issues, where we focuses only on resource management problems like allocation of resources or VMs, herewith, provides novel allocation
process for balancing the load in cloud system, and genetic methods for checking the feasibilities of cloud jobs before allocating to resources based on the cloud system configuration. First of all we define cloud system capacity of scheduling that the maximum rates at which tasks can be executed.
Then, we show that our selected cloud system is able to maximize the scheduling success rate sufficiently, which are initiated at any time and maintain the QoS parameters.
Keywords: Cloud Computing; Cloudsim; Latency; Resource Allocation; Utilization
Document Type: Research Article
Affiliations: 1: Department of Information Technology, SSN College of Engineering, Rajiv Gandhi Salai, OMR, Chennai 603110, TN, India 2: Department of ECE, Vignan’s University, Guntur 522213, Andhrapradesh, India
Publication date: 01 August 2017
- Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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