Abstract
Cloud services are broadly used in accomplishment, logistics, and computerized applications. It is not an easy technology, it consists of lots of issues like virtual machine management, scheduling of virtual machines, data security, providing resources (like hardware and software) and load balancing. The issue of load balancing arises in abundant applications but essentially they play an essential role in the application of cloud environment. Load balancing distributes a task into subtasks that can be performed together and mapping each of these programs to computational resources like a computer or a processor, the complete processor time will be decreased with upgrade processor usage. To solve the issue of load balancing various algorithms are proposed by authors in the recent past and one of them is genetic algorithms. The paper describes insight survey some genetic load balancing algorithms used in a cloud environment by taking into consideration different factors, further we have analyzed and correlated all these factors in order to do a comparative assessment based upon different parameters so as to identify the proficiency of different genetic algorithms
Publisher
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Subject
Electrical and Electronic Engineering,Mechanics of Materials,Civil and Structural Engineering,General Computer Science
Cited by
3 articles.
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1. A review on dynamic load balancing algorithms;2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS);2022-11-04
2. Genetic Approach based Optimized Load Balancing in Cloud Computing: A Performance Perspective;2022 9th International Conference on Computing for Sustainable Global Development (INDIACom);2022-03-23
3. Load balancing techniques in cloud computing environment: A review;Journal of King Saud University - Computer and Information Sciences;2021-03