Research Area: Edge Computing
In this thesis, we investigate and develop new methods for efficient and functional use of resources in edge networks. Setting this work aside from previous work, we study User Generated Content (UGC) such as social media information and data generated in the new emerging Internet of Things systems. We present efficient solutions for placing such content and managing which network resources should be used to make the edge networks effective. By effective we for example mean; using little energy, processing data with short delay or carrying out their tasks with little load on the network. In order to achieve this, we have used a range of optimization and control theoretic tools and studied different aspects of content and resource management in operator managed content distribution networks (CDN).
we took the data center viewpoint of a delivery system. We designed scheduling and request assignment algorithms with an energy usage objective. We showed that an energy-efficient dynamic server provisioning (DSP)-based assignment may lead to an unstable system if sufficient care has not be taken. We then investigated ways of keeping the servers stable, energy efficient and performing load balancing to provide better quality of service (QoS) for end users.
Name of the Researcher: Safavi, Mohammadhassan
Name of the Supervisor(s): Bjorn Landfeldt, Emma Fitzgerald, Saeed Bastani
Year of Completion: 2020
University: Lund University
Thesis Link: Home Page Url
