Author
Listed:
- Dawit Mekonnen
- Alemayehu Megersa
- Rakesh Kumar Sharma
- Durga Prasad Sharma
- Vimal Shanmuganathan
Abstract
Cloud services are accessed from different geographical locations where client migration or switching from one server to another based on the loads is a common phenomenon. One of the most critical challenges the cloud data centers face is managing the loads over geographically dispersed data centers and their virtual machines (VMs). VMs need to be balanced with the varied loads or dynamics of traffic. There are possibilities of the highest loads to be tolerated by the VMs over the cloud servers without crashing. Load balancing issues are managed by load balancing algorithms. Load balancing algorithms have varied issues of efficiency due to certain parameters like the capability of the lowest resource utilization, response time, higher overhead while checking the idle or normal nodes, and many others. Throttled load balancing algorithm manages loads of the virtual machines by dividing the virtual machines into two segments, that is, “available†and “free.†To do this, the throttled algorithm uses a single component to assign the virtual machines and other tasks. The throttled algorithm utilizes only the first VMs available, the next, and so on. These strategic issues most often degrade the performance of the applied load balancing algorithm. Such issues create a curiosity to enhance this algorithm’s performance for efficiently managing the dynamic loads of the cloud VMs. This research paper proposes a component-based throttled load balancing algorithm with VM reader, free VM holder, and free VM manager components. The VM reader component reads all available VMs. The free VM component holds free VMs temporarily until they are moved to the free VM manager component. For the performance test, the cloud analyst simulation tool was used. Based on the comparative analysis with the other five popularly used load balancing algorithms, the component-based algorithm’s performance is significantly enhanced. The proposed algorithm resulted in 325.30-microsecond response time and 27.12-microsecond processing time by the closest data center service broker policy. The newly proposed “component-based throttled load balancing algorithm†is found to be better than the existing throttled algorithm and the other five selected algorithms in terms of response time, processing time, and resource utilization.
Suggested Citation
Dawit Mekonnen & Alemayehu Megersa & Rakesh Kumar Sharma & Durga Prasad Sharma & Vimal Shanmuganathan, 2022.
"Designing a Component-Based Throttled Load Balancing Algorithm for Cloud Data Centers,"
Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, October.
Handle:
RePEc:hin:jnlmpe:4640443
DOI: 10.1155/2022/4640443
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