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Policies for Advanced Dynamic Load Balancing in Cloud Computing
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Author(s): Dharmesh Dhabliya (Department of Information Technology, Vishwakarma Institute of Information Technology, India), Sukhvinder Singh Dari (Symbiosis Law School, Symbiosis International University, India), Nitin N. Sakhare (Department of Computer Engineering, BRACT'S Vishwakarma Institute of Information Technology, India), Anish Kumar Dhablia (Altimetrik India Pvt. Ltd., India), Digvijay Pandey (Department of Technical Education, Government of Uttar Pradesh, India), A Shaji George (Almarai Company, Riyadh, Saudi Arabia), A. Shahul Hameed (Department of Telecommunication, Consolidated Techniques Co. Ltd., Riyadh, Saudi Arabia)and Pankaj Dadheech (Swami Keshvaand Institute of Technology, Management, and Gramothan, India)
Copyright: 2024
Pages: 14
Source title:
Innovations in Engineering and Food Science
Source Author(s)/Editor(s): Shilpa Mehta (Auckland University of Technology, New Zealand), Fakhar Islam (NUR International University, Pakistan)and Ali Imran (Government College University, Pakistan)
DOI: 10.4018/979-8-3693-0819-6.ch005
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Abstract
Cloud computing involves virtualization, distributed computers, networking, software, and web services. Clouds have servers, datacenters, and customers. It has fault tolerance, high availability, scalability, flexibility, little user overhead, low ownership cost, on-demand services, etc. These issues demand a robust load balancing mechanism. Balanced load distribution improves resource use and task response time by preventing some nodes from being completely loaded and others idle. Load balancers match processor and network node performance. A load balancing solution that improves throughput and latency for application-based virtual topologies with variable cloud sizes will apply the divisible load scheduling theorem.
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