Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Cloud computing allows multiple users to access computing resources and services in the cloud. However, numerous challenges emerge throughout information sharing, like task scheduling in cloud computing. This article defines load balancing as a technique for evenly distributing workflow across all structure endpoints to maximize resource consumption and user acceptance. It facilitates the distribution and de-allocation of modeling in the task without collapse. This work presents a novel dynamic load balancing technique. The suggested load balancer shortens the completion response period throughout wide data applications run on the public cloud. Workforce planning is just an NP-hard problem that needs addressing. Our suggested methodology offers ways to minimize the search effort, resulting in a load balancing process that is less complicated. An experimental result demonstrates the performance of the proposed method in terms of better response time, less number of work migrations, and less waiting time
"Dynamic Load Balancing Model for Efficient Work Load Distribution in Cloud Computing", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.3, Issue 2, page no.86 - 90, February-2018, Available :http://www.ijrti.org/papers/IJRTI1802015.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator