Code of Paper "Joint Task Offloading and Resource Optimization in NOMA-based Vehicular Edge Computing: A Game-Theoretic DRL Approach", JSA 2022.
A Realistic Mobile Edge Computing environment; with conditions for deadline and energy Energy-Constrained
Simulation code for "A max-min task offloading algorithm for mobile edge computing using non-orthogonal multiple access," by V. Kumar, M. F. Hanif, M. Juntti and L. -N. Tran, published in IEEE Transactions on Vehicular Technology, vol. 72, no. 9, pp. 12332-12337, Sept. 2023, doi: 10.1109/TVT.2023.3263791.
A lightweight framework that enables serverless users to reduce their bills by harvesting non-serverless compute resources such as their VMs, on-premise servers, or personal computers.
A Realistic, Versatile, and Easily Customizable Edge Computing Simulator.
Cognitive Generative Intelligent Task Offloading for Digital Twins of Vehicular Networks This repository contains the code and resources for the implementation of cognitive generative intelligent task offloading in digital twins for vehicular networks.
FDA Implementation on benchmark functions and Task-Offloading in Edge Cloud Environment
Mission Assignment and Task Offloading in Open RAN-based ITS This project provides the implementation of metaheuristic and deep reinforcement learning (DRL) algorithms for optimizing mission assignment and task offloading in Open RAN-enabled Intelligent Transportation Systems (ITS).
Integrated Terminal-Database CLI Framework
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