Avasalcai, C. F. (2021). Quality of Service aware Resource Management for Edge Systems [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.97062
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Demanding latency-sensitive applications have stringent requirements such as high availability and low latency. The current cloud-centric systems face challenges in satisfying the application’s stringent requirements. As a result, researchers have proposed two new paradigms, i.e., edge and fog computing, as an alternative to deploying demanding IoT applications closer to the edge of the network. By extending the cloud system with these two paradigms, we obtain an edge system. Edge systems have been identified as a solution to dis- tribute more resources closer to the end-user since meeting application demands must occur at runtime, facing uncertainty, and in a decentralized manner. However, the edge systems’ distributed nature makes the application development more challenging since the developer must divide the application’s functionality into multiple microservices. Furthermore, high volatility defines the edge system due to edge nodes being characterized by (i) heterogeneity and (ii) mobility, making a node unreliable – a node may fail or leave the network unexpectedly. As a result, the application deployment and management under volatility is more challenging. This calls for novel application development methodologies and resource management techniques that comply with the application’s requirements and aids the developer to develop, deploy, and manage an application in the target edge system. However, developing these techniques is not a trivial task. In this thesis, we provide novel methodologies and resource management frameworks to enable the efficient utilization of the edge node available resources and maintain the correct application functionality throughout its entire execution. Our objective is to (i) aid the developer during the application development process, (ii) deploy the latency-sensitive applications in the target edge system, and (iii) ensure that deployed applications remain operational during their lifespan.
Decentralization; Edge Computing; Resource Management; Application development; Internet of Things; Self-Adaptive