Developing a QoS and Spatially aware scalable fog system with adaptive cache

Akanni, Oluwashola Israel (2024) Developing a QoS and Spatially aware scalable fog system with adaptive cache. Masters thesis, Dublin, National College of Ireland.

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Abstract

With the expansion in the number of mobile systems integrated into IoT and fog networks, fog computing now includes scaling out and optimizing communication for mobile fog systems effectively. This research focuses on developing a QoS (Quality of Service) and spatially aware scalable fog system with an adaptive cache to enhance the efficiency and reliability of the system. In order to maintain a system that knows the approximate location of its devices even when they are constantly moving around. This is to optimize resource allocation, reduce latency, and improve the scheduling for these systems. Making use of existing ideas in fog computing, QoS provisioning, spatial awareness, and some caching techniques, a flat distributed network was developed which is also able to switch to a tiered network when offloading becomes required. The scheduler uses an adaptive cache to keep details of each fog Device in the configuration, it also is able to treat VMs on each fog device as independent machines while retaining QoS-aware properties such as Bandwidth and latency. Key performance metrics which were measured, analysed and compared against other possible more traditional fog systems without spatial awareness and adaptive caching were the energy and bandwidth usage and most importantly the savings in latency to show the new system’s efficiency. The application domain of choice is the autonomous car Industry, where latency-dependent decision-making could be crucial in averting disaster. The final results were able to show that keeping the system spatially aware was able to improve the QoS performance of the fog setup.

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:	25 Mar 2025 16:01
Last Modified:	25 Mar 2025 16:01
URI:	https://norma.ncirl.ie/id/eprint/7327

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