Today, with many IoT devices and the development of Internet technologies, both wired and wireless connectivity play a crucial role in offering a wide range of services to end-users. Moreover, such communication and networking technologies have influenced individuals, institutions, governments, and industries. As a result, communication technologies have become an indispensable part of daily life. Recently, Machine Learning (ML) technologies have achieved breakthrough advances. When combined with communication technologies, the achievement in AI has created unique applications such as smart cities, self-driving cars, etc.

Our research group focuses on the study and development of high-speed, dependable, and flexible networking technologies, using theoretical and practical techniques to incorporate social, information, device, and energy factors. We study to leverage AI in enhancing and optimizing network performance. We’re also looking into solutions for analyzing and mining data collected by IoT devices. See the slides here for more detail.

Contact: Dr. Nguyen Phi Le, Email:

Group website:

Research Directions

  • Network optimization: Exploiting machine learning, deep learning, reinforcement learning, meta-heurisctic techniques to optimize network performance.
  • Data mining in IoT networks: Focusing on processing, analyzing and mining data collected from IoT devices.
  • AI in networking: Applying various machine learning and deep learning techniques including graph networks, deep reinforcement learning, etc., to analyze and predict the network behavior. Leveraging AI in controlling network operations.
  • Distributed systems: Addressing different problems in distributed systems such as Synchronization, Replication and Consistency, Fault tolerance, etc.
  • New generation network: Solving problems of NGN in expanding the existing access network infrastructure into networks capable of satisfying the user’s requirements.
  • QoS-QoE: Proposing adaptive mechanisms to predict and optimize QoS/QoE in network systems.
  • Internet of Things: Addressing different issues of IoT systems such as security problems, lack of regulation, limited bandwidth, etc.

Research problems

  • Optimization problems in Wireless Rechargeable Sensor Networks: We focus on a new wireless charging paradigm that considers a variety of factors such as charging path, charging time, target coverage, and connectivity. Furthermore, our system considers various optimization goals, including minimizing the number of mobile chargers, optimizing the depot placement, and extending the network lifetime. To solve the problem, we go from theoretical modeling to applying state-of-the-art technologies. Specifically, we leverage reinforcement learning and deep reinforcement learning, fuzzy logic, genetic algorithms to propose novel charging algorithms for wireless rechargeable IoT networks.
  • Mobile air quality monitoring network: This research topic, part of the VinIF-funded Fi-Mi project (, presents a new mobile air quality monitoring network based on vehicle-mounted sensors. We explore various research issues, such as resource allocation, effective communication, data analysis, and data mining. The resource allocation problem is solved using optimization techniques such as reinforcement learning, fuzzy logic, and meta-heuristics. A mathematical model for opportunistic communication in mobile air quality monitoring networks is also proposed. We then leverage deep reinforcement learning for offloading data from devices to the servers. Finally, we use machine learning methodologies to calibrate the acquired data and propose deep learning models for spatiotemporal prediction problems.
  • Satellite precipitation calibration: We investigate a fascinating research problem that is how to calibrate the satellite precipitation data. Our method uses deep learning techniques to blend satellite data that is fine-grained but inaccurate with the coarse-but-accurate data from ground-based monitoring stations. We then leverage graph neural networks to model the spatial correlation between the ground-based monitoring stations. Besides, recurrent neural networks are utilized to capture the data’s temporal properties.
  • Prediction of water levels on rivers in Vietnam: This study focuses on data mining regarding river discharge and water levels in Vietnam. For hydrological research and flood prediction, forecasting river discharge and water levels have long been necessary. However, existing machine learning-based methods cope with severe flaws such as a lack of training data, noise in the obtained data, and the difficulty of altering the model’s hyper-parameters. In this research, we address at the same time these three challenges. Specifically, we apply data preprocessing techniques such as SSA to clean the data before feeding it into the forecasting models. Furthermore, we propose novel deep learning models that employ ensemble learning techniques and graph neural networks to capture both temporal and spatial correlation and extract relevant information from historical data. Furthermore, optimization techniques like metaheuristics are used to obtain the optimal hyper-parameters automatically.
  • Traffic prediction and intelligent routing: In this research, we study how to learn and predict networks’ future behavior dynamically. From that, we design algorithms to control the network operations efficiently and intelligently. Several research problems are taking into account, such as exploiting the Graph Neural Networks to capture the spatial relation of the network and then leveraging deep learning to predict the network traffic; using reinforcement learning to guide the packets; utilizing metaheuristic algorithms and linear programming to optimize the routing paths. We perform experiments on network simulators such as OMNET, NS2, and real datasets such as Brain, Abilene, and Geant.
  • Applying ML to Software-Defined Network =>  Knowledge-defined Network: Applying AI to the management of computer networks, making it to be a self-adaptive one. This means every network node will be an AI node, which is able to make decisions automatically. However, these network nodes have only a local view and a local control, hence, applying Artificial Intelligence to each network node is not trivial. For this purpose, a centralized control architecture, e.g. Software-defined Network (SDN), is a promising candidate. In this work, we decide to develop a knowledge layer on top of the SDN architecture, forming a Knowledge-defined Network.
  • Replication and consistency in heterogeneous and Distributed SDN networks: Proposing an East-West interface, called SINA, to provide the interoperability of a heterogeneous and distributed SDN network. In addition, a novel Reinforcement Learning-based consistency algorithm is introduced for an adaptive Quorum-based replication mechanism.
  • Applying Federated Learning to SDN: The learning phase of a multi-domain SDN network must address the following problems: both solutions of 1) learning separately in each domain and 2) collecting all data from different controllers and launching the training phase in a centralized server are not efficient due to the computational cost, training time, and the accuracy. That motivates us to apply Federated Learning, in which distributed SDN controllers cooperatively train a centralized learning model while do not share the training data for preserving data privacy.

Team Members

Dr. Nguyen Phi Le
Team Leader

Dr. Tran Hai Anh

Assoc. Prof. Do Phan Thuan

Dr. Nguyen Thanh Hung

Assoc. Prof. Tran Quang Duc

Latest Publications

Publications in 2021

  1. Tran Bao Hieu, Nguyen Duc Anh, Hoang Duc Viet, Nguyen Manh Hiep, Pham Ngoc Bao Anh, Hoang Gia Bao, Bui Hai Phong, Thanh Hung Nguyen, Nguyen Phi Le, Le Thi Lan. MC-OCR Challenge 2021: A Multi-modal Approach for Mobile-Captured Vietnamese Receipts Recognition. 2021 RIVF International Conference on Computing and Communication Technologies (RIVF). Hanoi, Vietnam. 19/08/2021
  2. Phi Le Nguyen, Yusheng Ji, Minh Khiem Pham, Hieu Le, Thanh Hung Nguyen. (1+epsilon)2- and Polynomial-Time Approximation Algorithms for Network Lifetime Maximization with Relay Hop Bounded Connected Target Coverage in WSNs. IEEE Sensors. 9577 - 9599. 13/01/2021
  3. Thuy Dung Nguyen, Tuyen Nguyen, Thanh Hung Nguyen, Kien Nguyen, Phi Le Nguyen. Joint Optimization of Charging Location and Time for Network Lifetime Extension in WRSNs. IEEE Transactions on Green Communications and Networking. 11/11/2021
  4. Khanh-Van Nguyen, Chi-Hieu Nguyen, Phi Le Nguyen, Tien Van Do, Imrich Chlamtac. Energy-efficient routing in the proximity of a complicated hole in wireless sensor networks. Wireless Networks -Springer. 01/01/2021
  5. Van An Le, Tien Thanh Le, Phi Le Nguyen, Huynh Thi Thanh Binh, Yusheng Ji. Multi-time-step Segment Routing based Traffic Engineering Leveraging Traffic Prediction. IFIP/IEEE International Symposium on Integrated Network Management. 1-8. France. 17/05/2021
  6. Tran Thi Huong, Le Van Cuong, Ngo Minh Hai, Nguyen Phi Le, Le Trong Vinh, Huynh Thi Thanh Binh. A bi-level optimized charging algorithm for energy depletion avoidance in wireless rechargeable sensor networks. Applied Intelligence. 1-23. 16/08/2021
  7. Kien Nguyen, Phi Le Nguyen, Li Zhe-tao, Hiroo Sekiya. Empowering 5G Mobile Devices with Network Softwarization. IEEE Transactions on Network and Service Management. 30/06/2021
  8. Thanh Thi-Hien Duong, Manh Nguyen Huu, Hai Nghiem Thi, Thi-Lan Le, Phi-Le Nguyen, Quoc-Cuong Nguyen. Visual-guided audio source separation: an empirical study. 2021 International Conference on Multimedia Analysis and Pattern Recognition (MAPR). Hanoi. 15/10/2021
  9. Phi Le Nguyen, Nang Hung Nguyen, Tuan Anh Nguyen Dinh, Khanh Le, Thanh Hung Nguyen, Kien Nguyen. QIH: an Efficient Q-learning Inspired Hole-Bypassing Routing Protocol for WSNs. IEEE Access. 20/08/2021
  10. Manh Hung Dinh, Ngoc Thach Hoang, Mai Phuong Nguyen, Phi Le Nguyen, Phan Thuan Do. Node Deployment Optimization for Target Coverage and Connectivity in WSNs with a Delay-constrained Mobile Sink. ICCE 2020. Phu Quoc Island. 13/01/2021
  11. Minh Hieu Nguyen, Phi Le Nguyen, Kien Nguyen, Van An Le, Thanh-Hung Nguyen, Yusheng Ji. PM2.5 Prediction Using Genetic Algorithm-based Feature Selection and Encoder-Decoder Model. IEEE Access. 57338 - 57350. 05/04/2021
  12. Anh Duy Nguyen, Viet Hung Vu, Minh Hieu Nguyen, Duc Viet Hoang, Thanh Hung Nguyen, Kien Nguyen, and Phi Le Nguyen. Efficient Prediction of Discharge and WaterLevels Using Ensemble Learning andSingular-Spectrum Analysis-based Denoising. The 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems IEA/AIE 2021. 24/07/2021
  13. Van An Le, Tien Thanh Le, Phi Le Nguyen, Huynh Thi Thanh Binh, Rajendra Akerkarx, Yusheng Ji. GCRINT: Network Traffic Imputation Using Graph Convolutional Recurrent Neural Network. IEEE International Conference on Communications. 1-8. Canada. 14/06/2021
  14. Phi Le Nguyen, Van Quan La, Anh Duy Nguyen, Thanh Hung Nguyen, Kien Nguyen. An On-demand Charging for Connected Target Coverage in WRSNs using Fuzzy Logic and Q-learning. MDPI Sensors. 12/08/2021
  15. Van TONG, Sami SOUIHI, Hai Anh TRAN and Abdelhamid MELLOUK. Machine Learning based Root Cause Analysis for SDN Network. IEEE GLOBECOM 2021. 07/12/2021
  16. Van TONG, Sami SOUIHI, Hai Anh TRAN and Abdelhamid MELLOUK. SDN-Based Application-Aware Segment Routing for Large-Scale Network. IEEE Systems Journal. 06/11/2021
  17. Hai Nam Nguyen, Hai Anh Tran, Scott Fowler, Sami Souihi. A survey of Blockchain technologies applied to software-defined networking: Research challenges and solutions. IET Wireless Sensor Systems. 21/10/2021
  18. Duc-Huy LE, Hai-Anh TRAN, Sami SOUIHI, and Abdelhamid MELLOUK. An AI-based Traffic Matrix Prediction Solution for Software-Defined Network. IEEE International Conference on Communications (ICC), 2021. 01-06. Online. 14/06/2021
  19. Hai-Anh TRAN, Thi-Thanh-Tu NGUYEN, Sami SOUIHI, and Abdelhamid MELLOUK. Towards a Novel Congestion Notification Algorithm for a Software-Defined Data Center Networks. IFIP/IEEE International Symposium on Integrated Network Management, 2021. 99-106. Bordeaux, France. 17/05/2021
  20. Duc-Huy LE, Hai-Anh TRAN, and Sami SOUIHI. A Reinforcement Learning-based solution for Intra-domain Egress Selection. IEEE International Conference on High Performance Switching and Routing (HPSR21). 01-06. Paris, France. 07/06/2021
  21. The-Anh Le, Quyet-Thang Huynh, Thanh-Hung Nguyen. A New Method to Improve Quality Predicting of Software Project Completion Level. Industrial Networks and Intelligent Systems, INISCOM 2021. 211-219. Hanoi. 22/04/2021
  22. Phan Thuan Do, Thi Thu Huong Tran, Vincent Vajnovszki. The equidistribution of some Mahonian statistics over permutations avoiding a pattern of length three. Discrete Mathematics. 112684. 09/10/2021
  23. Viet Dung Nguyen ; Ba Thai Pham ; Phan Thuan Do. Efficient algorithms for maximum induced matching problem in permutation and trapezoid graphs. Fundamenta Informaticae. 257-283. 22/07/2021

Publications in 2020

  1. 5Le Hoai Anh, Chu Manh Hai, Nguyen Phu Truong, Thanh-Hung Nguyen, Phi Le Nguyen. Optimal Deployment of Vehicular Mobile Air Quality Monitoring Systems. 2020 7th NAFOSTED Conference on Information and Computer Science (NICS). 26/11/2020
  2. La Van Quan, Thanh Hung Nguyen, Phi Le Nguyen. Extending Network Lifetime by Exploiting Wireless Charging in WSN. RIVF 2020. 15/10/2020
  3. Phi Le Nguyen, Thanh Hung Nguyen, Kien Nguyen. A Dynamic Routing Protocol for Maximizing Network Lifetime inWSNs with Holes. soict 2019. Hạ Long, Việt Nam. 04/12/2019
  4. Viet Dung Nguyen, Phi-Le Nguyen, Trung Hieu Nguyen, Kien Nguyen, Phan-Thuan Do. An $\frac{e-1}{2e-1}$-Approximation Algorithm for Maximizing Coverage Capability in Mobile Air Quality Monitoring Systems. 19th NCA 2020. Cambridge, MA, USA. 24/11/2020
  5. Huong Tran, Thi Thanh Binh Huynh, Phi Le Nguyen, Cao Thanh Long Doan, Dinh An Vuong, Trong Vinh Le. Optimizing Charging Locations and Charging Time for Energy Depletion Avoidance in Wireless Rechargeable Sensor Networks. CEC 2020. 1-8. UK. 19/07/2020
  6. Tran Thi Huong, Phi Le Nguyen, Huynh Thi Thanh Binh, Kien Nguyen, Ngo Minh Hai, Le Trong Vinh. Genetic Algorithm-based Periodic Charging Scheme for Energy Depletion Avoidance in WRSNs. WCNC 2020. 1-8. Virtual. 25/05/2019
  7. Huynh Thi Thanh Binh, Nguyen Phi Le, Nguyen Binh Minh, Trinh Thu Hai, Ngo Quang Minh, Do Bao Son. A Reinforcement Learning Algorithm for Resource Provisioning in Mobile Edge Computing Network. International Joint Conference on Neural Networks (IJCNN). 1-7. Online. 19/07/2020
  8. La Van Quan, Phi Le Nguyen, Thanh-Hung Nguyen, Kien Nguyen. Q-learning-based, Optimized On-demand Charging Algorithm in WRSN. The 19th IEEE International Symposium on Network Computing and Applications (NCA 2020). 24/11/2020
  9. Phi Le Nguyen, Ren-Hung Hwang, Pham Minh Khiem, Kien Nguyen, Ying-Dar Lin. Modeling and Minimizing Latency in Three-tier V2X Networks. The 2020 IEEE Global Communications Conference (IEEE GLOBECOM). 07/12/2020
  10. Bao Hieu Tran, Thanh Le-Cong, Huu Manh Nguyen, Duc Anh Le, Thanh Hung Nguyen, Phi Le Nguyen. SAFL: A Self-Attention Scene Text Recognizer with Focal Loss. 19th IEEE International Conference On Machine Learning And Applications (ICMLA 2020). 14/11/2020
  11. Viet-Dung Nguyen, Phi Le Nguyen, Trung Hieu Nguyen, Phan Thuan Do. A 1/2 -Approximation Algorithm for Target Coverage Problem in Mobile Air Quality Monitoring Systems. GLOBECOM 2020. Taipei, Taiwan. 07/12/2020
  12. Phi Le Nguyen, Thanh Hung Nguyen, Kien Nguyen. A Path-Length Efficient, Low-Overhead, Load-Balanced Routing Protocol for Maximum Network Lifetime in Wireless Sensor Networks with Holes. Sensors. 28/04/2020
  13. Lamine AMOUR, Van TONG, Sami SOUIHI, Hai Anh TRAN and Abdelhamid MELLOUK. Quality Estimation Framework for Encrypted Traffic (Q2ET). IEEE Global Communications Conference (GLOBECOM). 01-06. Hawaii, USA. 09/12/2019
  14. Sonxay Luangoudom, Duc Tran, Tuyen Nguyen, Hai Anh Tran, Giang Nguyen, Quoc Trung Ha. svBLOCK: Mitigating Black Hole Attack in Low-power and Lossy Networks. International Journal of Sensor Networks. 77-86. 05/01/2020
  15. Le Duc-Huy, and Hai-Anh Tran. A novel Machine Learning-based Network Intrusion Detection System for Software-Defined Network. 7th IEEE NAFOSTED Conference on Information and Computer Science (NICS), 2020. 25-30. thành phố HCM, Việt Nam. 26/11/2020
  16. Nguyen Thi My Binh, Abdelhamid Mellouk, Huynh Thi Thanh Binh, Le Vu Loi, Dang Lam San, Tran Hai Anh. An Elite Hybrid Particle Swarm Optimization for Solving Minimal Exposure Path Problem in Mobile Wireless Sensor Networks. Sensors. 2586. 01/05/2020
  17. Van TONG, Sami SOUIHI, Hai Anh TRAN, and Abdelhamid MELLOUK. Service-centric Segment Routing Mechanism using Reinforcement Learning for Encrypted Traffic. 16th International Conference on Network and Service Management (CNSM) 2020. 01-05. 02/11/2020
  18. Duc-Man Nguyen, Quyet-Thang Huynh, Nhu-Hang Ha, and Thanh-Hung Nguyen. Automated Test Input Generation via Model Inference Based on User Story and Acceptance Criteria for Mobile Application Development. International Journal of Software Engineering and Knowledge Engineering. 399-425. 30/06/2020
  19. Thanh Tam Nguyen, Thanh Dat Hoang, Minh Tam Pham, Tuyet Trinh Vu,Thanh Hung Nguyen, Quyet-Thang Huynh, Jun Jo. Monitoring agriculture areas with satellite images and deep learning. Applied Soft Computing. 1-16. 23/07/2020
  20. Nguyen Thi Thu Trang, Nguyen Hoang Ky, Hoang Son, Nguyen Thanh Hung, Nguyen Danh Huan. Natural Language Understanding in SmartDialog - a Platform for Vietnamese Intelligent Interactions. International Conference on Natural Language Processing and Information Retrieval NLPIR 2019. 01/06/2019
  21. Quyet-Thang Huynh, The-Anh Le, Thanh-Hung Nguyen, Nhat-Hai Nguyen, Duc-Hieu Nguyen. A Method for Improvement the Parameter Estimation of Non-linear Regression in Growth Model to Predict Project Cost at Completion. The 2020 RIVF International Conference on Computing & Communication Technologies (RIVF). 232-237. RMIT University, Vietnam. 21/07/2020
  22. The-Anh Le, Quyet-Thang Huynh, Thanh-Hung Nguyen, Nhat-Hai Nguyen, Phuong-Nam Cao. A Method for Conference Project Completion Cost Predicting Using LSTM in Earned Value Management Technique. 4th International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom), Hanoi, Vietnam, 2020. 87-92. 28/08/2020
  23. Huong Mai Dinh, Dung Viet Nguyen, Long Van Truong, Thuan Phan Do, Thao Thanh Phan, Nghia Duc Nguyen. Cycle time enhancement by simulated annealing for a practical assembly line balancing problem. Informatica. 127-138. 01/06/2020
  24. Phan Thuan Do, Ba Thai Pham, Viet Cuong Than. Latest Algorithms on Particular Graph Classes. Olympiads in Informatics. 21-35. 15/03/2020
  25. Đinh Mai Hương, Trương Văn Long, Đỗ Phan Thuận, Phan Thanh Thảo. Application of Exhaustive Search for Optimization Assembly Line Balancing in Garment Industry. Journal of Science and Technology, Technical Universities. 34-41. 01/12/2019
  26. Sonxay Luangoudom, Duc Tran, Nguyen Linh Giang. Lightweight Encryption Schemes for the Internet of Things: A review. Journal of Science & Technology. 53-57. 30/06/2020