Genetic Load Balancing Algorithms in Cloud Environment
Neha Sharma1, Jaspreet Singh2, Rohit Bajaj3

1Neha Sharma, (CSE) Scholar Chandigarh University, Mohali, Punjab, India.

2Jaspreet Singh, Department of CSE, Chandigarh University, Mohali, Punjab, India.

3Rohit Bajaj, Department of CSE, Chandigarh University, Mohali, Punjab, India.

Manuscript received on 21 September 2019 | Revised Manuscript received on 30 September 2019 | Manuscript Published on 01 October 2019 | PP: 98-103 | Volume-8 Issue-9S4 July 2019 | Retrieval Number: I11140789S419/19©BEIESP | DOI: 10.35940/ijitee.I1114.0789S419

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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.

Keywords: Cloud computing, Load balancing, Genetic Algorithm for Load Balancing.
Scope of the Article: Cloud Computing