Resource Planning and Allocation in Distributed Cloud Networks using Voids in Scheduled Intervals
V. Murali Mohan1, K.V.V. Satyanarayana2
1V. Murali Mohan, Research Scholar, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
2K.V.V. Satyanarayana, Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
Manuscript received on 25 August 2019 | Revised Manuscript received on 11 September 2019 | Manuscript Published on 17 September 2019 | PP: 1840-1847 | Volume-8 Issue-2S8 August 2019 | Retrieval Number: B11660882S819/2019©BEIESP | DOI: 10.35940/ijrte.B1166.0882S819
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The significant objective of research in the distributed cloud networks is resource planning and allocation using voids in scheduled intervals, which grabbed several researchers’ attention in contemporary literature. Minimum failures of resource scheduling, completion of a robust task and fair usage of the resource were the important parameters of resource scheduling schemes. Therefore, this paper projected scalable-resource scheduling method for distributed CC environments, which aimed to attain the metrics of scheduling. The projected method is known as “Resource Planning and Allocation in Distributed Cloud Networks using Voids in Scheduled Intervals (RPA-DCN),” where resources are scheduled towards the corresponding task so that, the optimum using of idle time of resource is attained. The projected method performs scheduling in sequential order, and they were allocation of optimum resource when no single resource is identified to allocate, then optimum manifold idle resources are allocated with a considerable filling of schedule intervals. This paper discusses (a) pre-requisite of resource scheduling schemes, (b) current scheduling methods found in recent literature, (c) methods & materials utilized and method of projected resource scheduling scheme (d) and its significance over other standard methods. The analysis of performance for the proposal conducted by metrics cross-validation such as load vs. loss, optimality of task completion & process-overhead in the resource-scheduling. Here, the simulation outcomes exhibit that the projected method is robust and scalable under modified metrics.
Keywords: RPA-DCN, Cloud Computing, Hadoop Cluster, DPSA, MGBA.
Scope of the Article: Cloud Computing and Networking