Edge/cloud resource management for time-sensitive applications

• Main Author: Woon, Yoke Min
• Other Authors: Arvind Easwaran
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Engineering::Computer science and engineering::Computer systems organization::Computer system implementation
• Online Access: https://hdl.handle.net/10356/165892
• Institution: Nanyang Technological University

The emergence of computationally intensive Artificial Intelligence technologies has been a major factor in the adoption of cloud computing as the standard architecture across many industries. Conversely, decentralisation of cloud computing in the form of edge and mobile computing is also occurring with the rise in popularity of the Internet of Things (IoT). There has been an increase in the number of mobile applications which typically result in high energy consumption and require powerful computation capacity (e.g. running ARVR, speech recognition etc.) In this project, we will study how these Smart Mobile Terminals (SMTs) can offload their computation tasks to Mobile Edge Computing (MEC) servers. MECs provide a cloud computing capacity near mobile users. We will consider 2 concepts: namely cooperative computation offloading and resource allocation. This involves optimising the allocation of resources among multiple devices, such as by using game theory or other optimization techniques, as well as developing algorithms for efficiently offloading computational tasks to the edge of the network. The eventual goal is to enable mobile devices to perform complex computational tasks more efficiently and with better performance, by leveraging the resources of the edge network and coordinating the allocation of those resources among multiple devices.