Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/594144
Title: Customizing the container orchestration and improving the performance of clustered iot services
Researcher: Aruna, K
Guide(s): Pradeep, G
Keywords: Computer Science
Computer Science Hardware and Architecture
Engineering and Technology
lightweight virtualization
orchestration
University: Anna University
Completed Date: 2024
Abstract: Container technology is the latest lightweight virtualization technology and it is an alternate solution for virtual machines. It is highly significant in many technologies and communication systems. Among the container technologies, Docker is widely acknowledged and most popular one. Containers, in general, have gained significant popularity due to their suitability for various IT environments including dynamic development, packaging and transferring from one environment to another environment. To maximize the container efficiency, scaling is essential to dynamically adjust the instances for optimal resource usage and adaptability to the changing workloads. The proposed research work focuses on four main aspects. The first work aims to develop a load-balancing scheduling algorithm that efficiently distributes the containers across the hosts especially in scenarios with a high number of running containers. In order to achieve the efficiency in load balancing and resource allocation of multiple containers, an Ant Colony Optimisation-based Light Weight Container (ACO-LWC) load balancing scheduling algorithm is proposed. This algorithm is specifically designed for scheduling various processing requests in a system. The performance metrics such as node load, response time (ms), Mean Square Error (MSE), Central Processing Unit usage (CPU) and Memory performance of the proposed algorithm are evaluated and compared with the existing baseline algorithms such as least connection and round robin algorithms. The quantitative analysis shows that the proposed ACO-LWC scheme achieves better performance in terms of all the metrics compared to the existing baseline algorithms.The second work focuses on container service migration which integrates with fog servers. newline
Pagination: xvii,160p.
URI: http://hdl.handle.net/10603/594144
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File230.11 kBAdobe PDFView/Open
02_prelim_pages.pdf2.48 MBAdobe PDFView/Open
03_content.pdf16.3 kBAdobe PDFView/Open
04_abstract.pdf9.1 kBAdobe PDFView/Open
05_chapter1.pdf888.41 kBAdobe PDFView/Open
06_chapter2.pdf405.93 kBAdobe PDFView/Open
07_chapter3.pdf1.2 MBAdobe PDFView/Open
08_chapter4.pdf847.41 kBAdobe PDFView/Open
09_chapter5.pdf1.04 MBAdobe PDFView/Open
10_chapter6.pdf353.49 kBAdobe PDFView/Open
11_annexures.pdf148.78 kBAdobe PDFView/Open
80_recommendation.pdf486.9 kBAdobe PDFView/Open
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