An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm
- Title
- An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm
- Creator
- Pani A.K.; Manohar M.; Thomas M.; Kumar P.
- Description
- Cloud computing has rapidly emerged as a burgeoning research field in recent times. However, despite this growth, a comprehensive examination of this domain reveals persistent issues in the application of cloud-based systems concerning workload distribution. The abundance of resources and virtual machines (VMs) within cloud computing underscores the importance of efficient task allocation as a critical process. Within the infrastructure as a service (IaaS) architecture, load balancing (LB) remains a pivotal but challenging task. The occurrence of overloaded or underloaded hosts/servers during cloud access is undesirable, as it leads to operational delays and system performance degradation. To address LB issues effectively, it is imperative to deploy a proficient access scheduling algorithm capable of distributing tasks across the available resources. A novel approach was introduced by combining the Harris hawks optimization and cuckoo search algorithm (HHO-CSA), with a specific focus on critical service level agreement (SLA) parameters, particularly deadlines, to uphold LB in a cloud environment. The primary objective of the hybrid HHO-CSA methodology is to provide task attributes, resource allocation, VMs prioritization, and quality of service (QoS) to clients within cloud computing applications. The outcome analysis reveals that the proposed hybrid HHO-CSA algorithm results in a resource utilization reduction of 52%, with an execution time of 529.84 ms and a makespan of 638.88 ms. These values outperform those of existing SLA-based LB algorithms. Effective task scheduling plays a pivotal role in ensuring the seamless execution of tasks within a cloud system, while LB significantly aligns with the SLAs available to users. Drawing insights from the existing literature, the suggested hybrid HHO-CSA method addresses the research gap by effectively mitigating the challenges. 2023, Accent Social and Welfare Society. All rights reserved.
- Source
- International Journal of Advanced Technology and Engineering Exploration, Vol-10, No. 105, pp. 1050-1062.
- Date
- 2023-01-01
- Publisher
- Accent Social and Welfare Society
- Subject
- Cloud computing; Hybrid Harris hawks optimization-cuckoo search algorithm; Load balancing; Quality of service; Service level agreement; Task scheduling
- Coverage
- Pani A.K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Manohar M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Thomas M., School of Computer Science, RV University, Bengaluru, India; Kumar P., Department of Computer Science and Engineering, Motihari College of Engineering, Bihar, India
- Rights
- All Open Access; Gold Open Access
- Relation
- ISSN: 23945443
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Pani A.K.; Manohar M.; Thomas M.; Kumar P., “An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/14098.