Mobile Edge Offloader Engine

Last updated on Oct 19, 2022
Code
The System Architecture

A mobile edge offloading engine that offloads task from mobile devices to edge and cloud servers based on cloud computation availability, mobile energy, and task execution time. It utilizes reinforcement learning to learn the environment without any previous knowledge.

Technology Used: Python, Reinforcement Learning, Mobile and Edge Simulation

Resource Management Mobile Edge Computing Reinforcement Learning
Md Rajib Hossen
Md Rajib Hossen
PhD Candidate in Computer Science

My research interests include Microservices, HPC, Distributed Systems, Machine Learning, and Converged Computing

Publications

Mobile Task Offloading Under Unreliable Edge Performance
In this paper, we propose a deep Q-learning based task offloading solution, DeepTO, for online task offloading. DeepTO learns edge server performance in a model-free manner and takes future battery needs of the mobile device into account.
Md Rajib Hossen, Mohammad A. Islam
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