Optimising Task Placement in Edge-Cloud Computing

Abstract

In this thesis, we address the challenges of task placement in edge-cloud computing environments by presenting a task placement model to overcome the limitations of traditional scheduling techniques. Our model aims to minimise delays associated with user requests by generating appropriate job placement strategies, supporting multi-user scenarios, and introducing a novel task duplication approach to mitigate transmission costs. Through our experiments, we demonstrate the effectiveness of our model in improving response times and meeting user deadlines, particularly in scenarios where conventional task-to-resource assignments would be impractical.