Title: Improved round-robin rule learning for optimal load balancing in distributed cloud systems
Authors: S. Sree Priya; T. Rajendran
Addresses: PG and Research Department of Computer Science, Government Arts & Science College (Affiliated to Bharathiar University, Coimbatore), Kangeyam-638108, Tamil Nadu, India ' PG and Research Department of Computer Science, Government Arts & Science College (Affiliated to Bharathiar University, Coimbatore), Kangeyam-638108, Tamil Nadu, India
Abstract: A newly emerging technology that distributes virtualised computer resources across the internet is referred to as 'cloud computing' and is gaining popularity. These clouds' ability to evenly distribute the load is vital. Load balancing in cloud computing distributes dynamic workloads so no database server is overcrowded or underloaded (LB). As a result, a dynamic load balancing technique in the cloud may contribute to improved service stability and resource utilisation. In this study, we model a load balancing system that balances the cloud's available resources using a rule-based round-robin method. Cloud parameters are used to calculate and allocate resources using a rule-based round-robin technique. The study analyses cloud metrics to determine cloud loads and resources. The cloud sim tool is used to allocate resources, and its effectiveness is tested against a variety of performance measures such as overhead, migration time, and throughput rate. Simulation results show that rule-based round-robin improves cloud performance. When compared to existing algorithms, the proposed methodology improves task performance by about 4%.
Keywords: optimisation; load balancing; cloud computing; rule-based round robin; overcrowded or underloaded (LB); cloud parameters; CloudSim-3.0.3; weighted round-robin technique; virtual machines.
International Journal of System of Systems Engineering, 2023 Vol.13 No.1, pp.83 - 99
Received: 07 Jun 2022
Accepted: 03 Aug 2022
Published online: 16 Feb 2023 *