A Systematic Analysis of Load Balancing in Cloud Computing

Abstract

Cloud Computing is an ever growing area in information technology. It is internet based technology which emphasizes its utility and follows pay-as-you-go model. It is at present turning into the favoured strategy for communication and computation over scalable networks because of various attractive qualities such as high accessibility, adaptability, scalability, simplicity of management, fault tolerance and minimal effort of possession. The data processing and storage volume is increasing rapidly in cloud environment, which prompts an uneven dissemination of overall work on cloud resources. So a legitimate balance of overall load balancing over the available resources is a major issue in cloud computing paradigm. It is a technique which uses multiple nodes and distributes dynamic workload among them so that no single node is overloaded. It enhances system performance and legitimate utilization of resources. It also limits the time and cost engaged with such huge computing models. Load balancing and better resource utilization is provided by many existing algorithms. This paper explores the various load balancing algorithms related to the cloud.

Bigdata and Machine Learning Models for Dimentionality Reduction Platform

“…In this hash analysis is main goal of the system; the dimensionality reduction has been performed with the help of rectangular outstanding column analysis. These frameworks correct the error dimensional reduction techniques [11][12][13][14][15][16][17][18][19][20][21]. This is the modern technique utilized for PCA, MDS linear and nonlinear applications respectively.…”