Performance Analysis of Cloud Analytics Across Multi Region Data Centres Using VM Scheduling Algorithms - Jha, Mayank Kumar; Kumar, Suman; Singh, Gurpreet (Indian Journal of Computer Science, 2026)
Cloud computing is widely used in today’s world as it can provide resources from different locations. However, when the cloud infrastructure is deployed over various locations such as America, Asia, and Europe, it is very difficult to achieve the performance. This is because each region has different kinds of users, different kinds of workloads, and different kinds of internet speeds. Because of this diversity, issues may occur. In this paper, we are going to discuss the performance of cloud analytics over a multiregion environment using various kinds of Virtual Machine (VM) scheduling algorithms. Instead of using the real cloud system, we have opted for a simulation approach for creating a virtual cloud system. In the virtual cloud system, multiple regions have been created with different data centres, users, and bandwidth conditions to simulate real-world scenarios. In this scenario, we have implemented various scheduling algorithms such as Round Robin, First Come First Serve (FCFS), Min-Min, and Max-Min scheduling algorithms and compared their performance. The system is simulated under all the conditions, and the results are obtained using key parameters such as response time, processing time, cost, throughput, and bandwidth. From all the analysis and results obtained in this study, we can conclude that there is no particular algorithm that performs better in all situations. Some algorithms are fast, while some are cost-effective. This study enables us to understand which scheduling algorithm is best for a particular cloud environment for the growth of cloud analytics performance.