Proposing a Load Balancing Algorithm For Cloud Computing Applications. Issue 1 (August 2021)

• Record Type: Journal Article
• Authors: Amal Murayki Alruwaili, Bayan A. Al; Humayun, Mamoona; Jhanjhi, NZ
• Is Part Of: Journal of physics. Volume 1979:Issue 1(2021)
• Publication Date: 2021-08
• Subjects: Cloud Computing (CC) -- Load balancing -- Machine Learning -- Algorithm -- Task Scheduling; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1979/1/012034
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: At the current time, one of the fields that are quickly developing in computing is clouding computing (CC). There are vital services needed by individuals as well as organizations that are offered in CC, namely IaaS, SaaS, and PaaS. Through the creation of the cloud, the development of the application has become easier, as well as providing services to end-users through virtualization over the internet. In CC, we have cloud service providers who deal with large computing structures completely defined on usage as they offer their services in a dependable mode. However; CC is facing the issue of load balancing, which impacts the performance and makes it weak if we overload the system. Developing an effective load balancing algorithm while utilizing CC efficiently is one of the providers' ultimate goal. Virtualization and scalability are other dynamic techniques which entail developing VMs in CC. Data traffic and Web services provision is growing each day; thus, load balancing is a major challenge in the field of CC and is increasing the importance of task scheduling as well. At this point in time, evolvement in CC necessitates the greater need for infrastructure and resource development. The load balancing policy guarantees the efficient usage of the resource through the provision of services to the cloud subscribers. Load balancing also prioritizes subscribers by using an appropriate schedule. As a contribution in research, this paper proposes an algorithm for load balancing in CC. Proposed algorithm enhance the performance of Cloud Computing applications