An Enhanced Load Balancing Algorithm for Cloud Enterprise Resource Planning (ERP) Data in a Multi-Cloud Environment

Arnold Mashud Abukari *

Department of Computer Science, Tamale Technical University, Tamale, Ghana.

Edem Kwedzo Bankas

Department of Business Computing, C. K. Tedam University of Technology and Applied Sciences, Ghana.

Mohammed Muniru Iddrisu

Department of Mathematics, C. K. Tedam University of Technology and Applied Sciences, Ghana.

*Author to whom correspondence should be addressed.


Abstract

Businesses and individuals have seen the need to adopt the cloud and mulit-cloud environment for their businesses and storage of data. The load balancing concerns especially in the multi-cloud environment was investigated and a new algorithm proposed. In this research, a proposed new load balancing algorithm is presented and compared with the Round Robin (RR) and Weighted Round Robin (WRR) algorithms. The proposed scheduling algorithm considered several Cloud ERP Data chunks to analyse the data transmission rate or throughput, the transmission delay, data loss and the Cloud ERP Data drop ratio. The proposed algorithm performed better compared to the Round Robin (RR) and Weighted Round Robin (WRR) in a multi cloud environment with data chunks above 150 in terms of throughput. The proposed algorithm again outperformed the RR and WRR with a recorded lower transmission delays and lower data loss.

Keywords: Load balancing, cloud computing, ERP, LBaaS


How to Cite

Abukari , Arnold Mashud, Edem Kwedzo Bankas, and Mohammed Muniru Iddrisu. 2023. “An Enhanced Load Balancing Algorithm for Cloud Enterprise Resource Planning (ERP) Data in a Multi-Cloud Environment”. Asian Journal of Research in Computer Science 16 (3):197-209. https://doi.org/10.9734/ajrcos/2023/v16i3356.

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