Resource Offloading (Balancing) in Cloud Environment using Particle Swarm Optimization and Improved Particle Swarm Optimization on Xen Server
Keywords:
Cloud Environment, Particle Swarm Optimization, Improved Particle Swarm Optimization, Type 1 Hypervisor, Xen Server.Abstract
Cloud has numerous strong servers to allot immense solicitation of clients. Load Balancing (Resource Offloading) is a strategy to disperse tasks on numerous VM’s of Server to accomplish Asset usage, Reduce Reaction (cost) time and keep away from trouble. Resource offloading is a crucial factor in ensuring that the available resources are utilized efficiently, and the workload is distributed optimally. This paper presents novel research of resource offloading in a cloud environment and explores the different approaches to resource offloading, including Resource offloading, and Response time reduction of VM. In this article, A PSO & Improved PSO, has been introduced to track down the better arrangement for the issue of Allotment Resources (Assets) and load adjusting in CC. This Work was probed Xen Server and aftereffect of the Proposed Calculation Further developed PSO was extremely uplifting. Altogether the aftereffect of IPSO contrasted and PSO Calculation.
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Kumaran K, Sasikala E. An efficient task offloading and resource allocation using dynamic arithmetic optimized double deep Q-network in cloud edge platform. Peer-to-Peer Networking and Applications. 2023 Feb 24:1-22.
Zavieh H, Javadpour A, Li Y, Ja’fari F, Nasseri SH, Rostami AS. Task processing optimization using cuckoo particle swarm (CPS) algorithm in cloud computing infrastructure. Cluster Computing. 2023 Feb;26(1):745-69.
Kouka N, BenSaid F, Fdhila R, Fourati R, Hussain A, Alimi AM. A novel approach of many-objective particle swarm optimization with cooperative agents based on an inverted generational distance indicator. Information Sciences. 2023 Apr 1;623:220-41.
Pirozmand P, Jalalinejad H, Hosseinabadi AA, Mirkamali S, Li Y. An improved particle swarm optimization algorithm for task scheduling in cloud computing. Journal of Ambient Intelligence and Humanized Computing. 2023 Feb 15:1-5.
Ismail HA, Riasetiawan M. CPU and memory performance analysis on dynamic and dedicated resource allocation using XenServer in Data Center environment. In2016 2nd International Conference on Science and Technology-Computer (ICST) 2016 Oct 27 (pp. 17-22). IEEE.
Dave A, Patel B, Bhatt G, Vora Y. Load balancing in cloud computing using particle swarm optimization on Xen Server. In2017 Nirma University International Conference on Engineering (NUiCONE) 2017 Nov 23 (pp. 1-6). IEEE.
Riasetiawan M, Ashari A, Endrayanto I. The analyses on dynamic and dedicated resource allocation on Xen server. TELKOMNIKA (Telecommunication Computing Electronics and Control). 2016 Mar 1;14(1):280-5.
Bist M, Wariya M, Agarwal A. Comparing delta, open stack and Xen Cloud Platforms: A survey on open source IaaS. In2013 3rd IEEE International Advance Computing Conference (IACC) 2013 Feb 22 (pp. 96-100). IEEE.
Dave A, Patel B, Bhatt G. Load balancing in cloud computing using optimization techniques: A study. In2016 International Conference on Communication and Electronics Systems (ICCES) 2016 Oct 21 (pp. 1-6). IEEE.
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