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Narawade, Rahul Dhanapal (2023) Enhanced Scheduling for KubeEdge nodes in Edge Computing using EdgeMesh. Masters thesis, Dublin, National College of Ireland.
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Abstract
Edge Computing processes data at the edge to reduce latency and deliver faster responses by reducing data that has to be synced with the cloud. Strategic load balancing plays a crucial role in maximizing IoT efficiency and reliability. KubeEdge commendably orchestrates containerized applications on edge nodes by extending Kubernetes and maintaining cloud-edge node networks. This facilitates the seamless load balancing and discovery of services on edge nodes through EdgeMesh. However, this approach could decrease KubeEdge cluster throughput and delay services due to the need to forward traffic between edge nodes in different locations. Therefore, a better scheduling algorithm is required than the current default algorithm. This paper presents a solution that uses EdgeMesh to strategically enhance load balancing to improve the KubeEdge cluster throughput. This solution utilizes the best possible nodes in the cluster to serve the user requests efficiently. The outcome of the study shows that the enhanced custom scheduling outperforms the default scheduling algorithms. The average response time was improved by approximately 33% and requests per second increased by approxmatly 94%. Overall, cluster throughput is enhanced by 63.5%.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Sahni, Vikas UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing |
| Divisions: | School of Computing > Master of Science in Cloud Computing |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 09 Apr 2025 13:48 |
| Last Modified: | 09 Apr 2025 13:48 |
| URI: | https://norma.ncirl.ie/id/eprint/7395 |
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