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Multiagent Communications and Networking Lab

MCNL members (May 2022)

Multiagent Communications and Networking Lab headed by Prof. Hyunggon Park is a research entity in the Department of Electronic and Electrical Engineering, College of Engineering, Ewha Womans University.

Our research has focused on machine learning based distributed decision making strategies for multi-agent network systems, intelligent and automatic resource management strategies for 5G network systems, efficient and robust data streaming strategies using network coding, big data analytics for Internet of Things (IoT) and data stream mining systems based on machine learning, fairness and optimality paradigms for resource management. All information about our current projects, with brief description of the results and the links to current publications, can be found on Research page.

We are actively recruiting graduate students and postdocs. If you are interested in our group, please send me an email with your CV (or resume).

Research

Research Topics

Artificial Intelligence and Machine Learning based Distributed Decision Making Strategies for Multi-agent Network Systems
Intelligent and Automatic Management/Orchestration Strategies for 5G Network Systems
Machine Learning based Data Analysis and Interaction Inference
Efficient and Robust Data Streaming Strategies using Network Coding
Fairness and Optimality Paradigms for Resource Management
Game Theoretic Approaches for Distributed Resource Management Schemes in Multiagent Systems

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Active Projects

Graph Neural Networks for Inter-separable Sparse Networks in 5G/B5G Funding Agency: National Research Foundation (NRF), Ministry of Science and ICT Principal Investigator (100,000 USD/year, Mar. 2020 - Feb. 2023) Summary: With the goal of building inter-separable sparse networks based on graph neural networks in 5G (5th Generation)/B5G (Beyond 5G) in a 5G/B5G network environment, we intend to develop a network data analytics and inference engine based on machine learning algorithms, an inter-separable sparse network algorithm that can independently support vertical services and an inter-separable network platform.
Supervised Agile Machine Learning Techniques for Network Automation based on Network Data Analytics Function Funding Agency: Institute for Information & Communication Technology Promotion (IITP), Ministry of Science and ICT Principal Investigator (400,000 USD/year, Apr. 2019 - Dec. 2021) Summary: For 5G network architecture that aims to provide multiple services based on network slicing in single physical network, network automation is essential. For this, we intend to develop algorithms that can analyze network data based on supervised machine learning, design a framework that enables rapid conversion (agile) of a network that can provide customized services, and automatically configure an adaptive and flexible optimal network for services in realtime. For this, we develop an algorithm that can determine the optimal network based on a deep neural network (DNN) and design a DNN to SDN (DNN2SDN) framework.
Language-Conditioning Processing System based on Connectionism Model and Machine Learning for Age-Related Language Impairment Prediction Funding Agency: Ewha Womans University Faculty Participant (100,000 USD/1.5 year, Jul. 2019 - Dec. 2020) Summary: We intend to develop a Korean language processing model that can diagnose the types of language processing impairment in the elderly by applying connectionism model and machine learning.

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Lectures
Spring/Fall 2020 Sabbatical Leave (No class) Fall 2019 Random Processes (Undergraduate) Course Evaluation Communications Lab (Undergraduate) Section I, Evaluation Section II, Evaluation Optimization Theory (Graduate) Spring 2019 Embedded System Design and Lab (Undergraduate) Course Evaluation Multimedia Mobile Communication Network (Graduate) more...

News

May 2020: A journal paper, "Non-iterative Coordinated Beamforming for Multicell MIMO Heterogeneous Networks" authored by Prof. Minhae Kwon and Prof. Hyunggon_Park , is published in Wireless Personal Communications. In this paper, we propose a low complexity algorithm for designing non-iterative beamforming vectors that can improve the signal to noise ratio in multicell MIMO heterogeneous networks.
Apr. 2020: Prof. Hyunggon Park gives an invited talk at the Samsung AI Center - Cambridge for "Multiagent Reinforcement Learning Approaches for Adaptive Network Topology Formation."
Apr. 2020: A Korean patent "Network Topology Formation for Mobile Sensor Networks based on Network Coding" has been issued.
Mar. 2020: The first Ph.D. of our lab, Dr. Minhae Kwon, is appointed as an Assistant professor in the School of Electronic Engineering and School of Computer Science & Engineering at the Soongsil University, Seoul, Republic of Korea, leading her research entity Brain and Machine Intelligent Lab..
Mar. 2020: A journal paper "Intelligent IoT Connectivity: Deep Reinforcement Learning Approach" authored by Dr. Minhae Kwon and researcher Juhyeon Lee is published in IEEE Sensors Journals.
Feb. 2020: A journal paper "Data Driven Reliable Dissemination Strategy Based Systematic Network Coding in V2I Networks" authored by Ph.D student Jungmin Kwon is published in The Journal of Korean Institute of Communications and Information Sciences (J-KICS).
Jan. 2020: A paper, "Efficient and Reliable Data Dissemination over Handover Dynamics in V2I Networks," authored by Ph.D. student Jungmin Kwon is presented in IEEE International Conference on Consumer Electronics (IEEE ICCE 2020)(Las Vegas, USA).
Dec. 2019: A research project, 'Graph neural networks for inter-separable sparse networks in 5G/B5G' is funded by National Research Foundation (NRF) of Korea.
Nov. 2019: A paper, "Research on the measurement of data transmittable mobile node distribution based on transmisson powers," authored by the 2019 summer interns (Miseon Yu, Minkyung Kim and Serae Kim) and Ph.D. student Jungmin Kwon is awarded by KICS.
Nov. 2019: Prof. Hyunggon Park is selected as the 2019 LG Yonam Academic Support Programs, supported by LG Yonam Foundation.
Oct. 2019: M.S. student Daeun Jung is selected as Intensive Program in Artificial Intelligent at Carnegie Mellon University, US, supported by IITP.
Oct. 2019: A conference paper "Efficient and Reliable Data Dissemination based on Systematic Network Coding in V2I Networks" authored by Ph.D. student Jungmin Kwon is accepted for publication in IEEE International Conference on Consumer Electronics (IEEE ICCE 2020) (Las Vegas, USA).
Sep. 2019: A conference paper "Reliable Data Dissemination Strategy based on Systematic Network Coding in V2I Networks" authored by Ph.D. student Jungmin Kwon is accepted for publication in International Conference on ICT Convergence (ICTC 2019) (Jeju, Korea).
Sep. 2019: Hyunggon Park 2019 Young Engineering Education Award from Korean Society for Engineering Education
Jul. 2019: A journal paper "Distributed Topology Design for Network Coding Deployed Networks" authored by Dr. Minhae Kwon is accepted for publication in Signal Processing
Apr. 2019: A paper "An Iterative Algorithm of Key Feature Selection for Multi-class Classification" authored by M.S. student Daeun Jung is accepted for publication in International Conference on Ubiquitous and Future Networks (ICUFN 2019).
Apr. 2019: A Korean Patent "A Method and Apparatus for Network Formation in Dynamic Networks" has been issued.