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Cloud computing involves using internet-based remote servers for data storage, management, and processing. This on-demand service allows users to make payments for simply that which they utilize. Since users of cloud computing are widespread globally, managing this vast amount of data presents a significant challenge. Load balancing efficiently allocates workloads across multiple computing resources, such as online servers. The load balancer's resources can be changed or added based on user requirements. The primary goals of load balancing are to optimize resource usage, costs, to enhance throughput, and to prevent VMs from being overloaded. This research work introduces a migration of jobs in virtual machines using the priority of tasks, remaining execution time as well as migration time for the cloud dynamic load balancing. The proposed method shows better result in comparison with some existing cloud load-balancing algorithms in respect of average makespan time, average response time.

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Priority-Based VM Migration with Dynamic Load Balancing in Cloud Environment

  • 会议论文

  • 发表日期：

    2026年

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  • Soumen Swarnakar,
  • Chandan Banerjee,
  • Debak Bhattacharjee,
  • Subhrajit Dhar,
  • Ankita Dhar,
  • Siddharth Roy,
  • Tanmay Dutta

摘要

Cloud computing involves using internet-based remote servers for data storage, management, and processing. This on-demand service allows users to make payments for simply that which they utilize. Since users of cloud computing are widespread globally, managing this vast amount of data presents a significant challenge. Load balancing efficiently allocates workloads across multiple computing resources, such as online servers. The load balancer's resources can be changed or added based on user requirements. The primary goals of load balancing are to optimize resource usage, costs, to enhance throughput, and to prevent VMs from being overloaded. This research work introduces a migration of jobs in virtual machines using the priority of tasks, remaining execution time as well as migration time for the cloud dynamic load balancing. The proposed method shows better result in comparison with some existing cloud load-balancing algorithms in respect of average makespan time, average response time.