GSOC2023ns3-ai

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Revision as of 01:17, 11 May 2023 by Muyuan (Talk | contribs) (Added Project Goals, Repository and About Me)

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Project Overview

Project Goals

The proposed project aims to enhance the ns3-ai module, which provides interfaces between ns-3 and Python-based ML frameworks using shared memory, with a focus on performance optimization and expanding the range of supported data structures. To achieve this, the project will introduce APIs for additional data structures like vector and string in shared memory IPC to reduce the interaction between C++ and Python. Additionally, the project will provide examples demonstrating how to implement ML algorithms within ns-3 using C++ and open-source frameworks such as TensorFlow and PyTorch. The project will also improve the current examples and documentation and integrate new examples, such as LTE handover. Overall, the project aims to expand and accelerate the capabilities of the ns3-ai module, enabling users to simulate and analyze large-scale networks with greater efficiency and flexibility.

Repository

https://github.com/ShenMuyuan/ns3-ai/tree/cmake

About Me

Education

As a junior at Huazhong University of Science and Technology, I am majoring in electronic engineering. I am proud to be a member of the Undergraduate Program for Advanced Project-based Information Science Education, also known as the Seed Class, and currently serve as the class monitor. Additionally, I am a project leader in the Dian group, where I engage in extracurricular technical projects. In terms of relevant coursework, I have excelled in network programming through courses such as C programming language and computer network, both of which I achieved a perfect grade point of 4.0. These courses have equipped me with a strong foundation in network programming, which I believe will enable me to contribute effectively to relevant projects. I am a motivated and skilled undergraduate student with a passion for network programming and a track record of academic excellence.

Experience with ns-3

During my academic journey, I have had the opportunity to explore computer networking through labs and projects. In particular, in the labs for the computer networking course, I gained valuable insights into how different parameters, such as the number of STAs, CW range, and packet arrival rate, can impact network throughput in the WiFi DCF protocol. In addition, I have worked on a project that leverages ns-3 as a simulation platform with Prof. Yayu Gao. Through this project, I have gained practical experience in simulating WiFi MAC rate control algorithms, which has further solidified my understanding of the ns-3's usage and its object-oriented programming approach. Overall, my hands-on experience in both labs and projects has allowed me to apply theoretical concepts to practical scenarios and enhanced my network simulation and analysis skills.

Milestones