Enhance Microservices Placement by Using Workload Profiling Across Multiple Container Clusters

Abdul Hameed Mohammed Farook, Shamir Ahamed (2022) Enhance Microservices Placement by Using Workload Profiling Across Multiple Container Clusters. Masters thesis, Dublin, National College of Ireland.

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Abstract

Companies use microservices to break up large, centralized applications into smaller, more manageable pieces that can be deployed and run in their own containers. Microservices are used by businesses to hasten product creation and upkeep, improve performance forecasting, and increase scalability. Using a task-based method, We may move only the additional workloads away from a stressed service and into a less taxed one, effectively balance the network. when there is a rise in demand for a service. Multiple versions of the system are frequently constructed to accommodate the high volume of responses. sharing network traffic amongst multiple far-flung computers. In this article, We looked at how to balance the workload of containerized microservices using a variety of flexible techniques. As a result of using cloud-based computing capabilities, microservices can make use of a distributed deployment model for their resources.

After reviewing the literature on existing methods and algorithms for load balancing, the findings indicate that further exploration concludes that further study is warranted. In this study, I have validated the PSO (Particle-Swarm-Optimization), SJF (Shorted Job First), FCFS (First Come, First Served), and RR (Round Robin) methods for microservice load balancing evaluation. A statistical analysis shows that the proposed technique is useful for reducing execution latency by picking the best load-balancing algorithm.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Heeney, Sean UNSPECIFIED
Uncontrolled Keywords:	MicroServices; Workloads; Task Scheduler; ContainerCloudSim; Cloudlet; VMs; Containers; Nodes
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:	Tamara Malone
Date Deposited:	18 Apr 2023 12:59
Last Modified:	18 Apr 2023 12:59
URI:	https://norma.ncirl.ie/id/eprint/6455

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