An Investigation of Various Cloud Load Balancing Techniques

Abstract

CONCLUSION and FUTURE SCOPE newlineConclusion newlineCloud computing is an on-demand service where consumers can access shared computer newlineresources at any time. Access to virtual resources over the internet is provided by a web-based newlineapplication. The more people who use the cloud, the greater the demand. The distribution of newlineprocessing burden to processing components is difficult to grasp. In order to keep each newlineprocessing unit at a constant workload, load balancing methods are employed. Random Load newlineBalancing is one of the strategies in Cloud Computing that allows resources to be allocated newlinebased on the number of user requests at any one time. To speed up the request process, this newlinesolution employs a randomization strategy. Testing this recommended load-balancing newlineapproach will be easy with Cloud Analyst. In order to compare the random approach to other newlinetechniques, a load balancing study is done. It is discovered that the response time is quicker newlinewhen using the suggested random strategy. PSO, Ant Colony, and Honey Bee algorithms are newlineall outperformed by the dynamic method proposed in this thesis. newlineFuture Work newlineThe workload on cloud computing is changing as a result of the rise of Internet of Things (IoT). newlineIoT applications offer a variety of services and workflows, and this is why this is necessary. newlineLoad balancing and job scheduling in the cloud may be different when IoT apps are present. newlineThis is why further research is needed in this area