Thank you for your interest in our laboratory.
Our laboratory has been closed due to the retirement of Prof. Fuchun Joseph Lin.
We were previously located in Microelecctronics and Information Systems Research Center (MIRC) of
National Chiao Tung University in Rooms 721-723.
Click on "Research Team" above to learn how to contact Prof. Lin.
Click on "Research Focuses" & "Funded Projects" above to discover the current activities of Prof. Lin.

We envisage a connected world where all things that can be connected will be provided with connectivity to the Internet. This is a new world expanding beyond human-to-human (H2H) communications and allowing machine-to-machine, machine-to-mobile and man-to-machine (M2M) communications. By this wide expansion of Internet connectivity via machines, the quality of human life can be greatly improved with increasing level of convenience and safety and with new methods of cost and time saving.
Lately, we focus in applying 5G networks, Fog Computing and AI to support M2M communications and IoT applications. In particular, we address research issues in Tackling IoT Scalability with 5G NFV-enabled Network Slicing, NFV-Enabled Hybrid Scalability for IoT Slice, Evaluating Dedicated Slices of Different Configurations in 5G Core, Enabling IoT/M2M System Scalability with Fog Computing and Distributed Artificial Intelligence enabled by Fog Networking.

Our Laboratory focuses on the research issues in enabling such a vision of M2M communications where all things possible are connected to the Internet to form the Internet of Things (IoT). Such an M2M network (represented by the outer circle in our lab logo) is structured into three major domains (represented by three inner circles of different colors in our lab logo): M2M area networks, M2M core network and M2M applications. The M2M area networks are where networks of sensors, devices and machines are deployed. The M2M core network connects the M2M area networks distributed in various application domains to the mobile broadband network such as 4G LTE/SAE or 5G/6G NR/Core. The M2M applications are built upon M2M service capabilities in both M2M area and core networks and involve many key technologies such as Cloud, Fog, SDN/NFV, Big Data, Machine Learning and AI. The objective is to provide the end users (either human or machine) with new capabilities that deliver convenience, safety, cost/time savings to people’s life.

Over the past few years, we have produced many research results in each of three major areas above. The list below gives the PhD/Master thesis topics of our lab members up to 2021.

2014
-Comparison and Analysis of M2M-Enabled Trip Planning Systems
-Converging MQTT resources in ETSI standards based M2M platform
-Improving Utilization and Customer Satisfaction of Parking Space with M2M Communications
-M2M-enabled Resource Allocation for Publicly Shared Facilities
2015
-Incorporating OMA DM Lightweight Protocols in M2M Standard Architecture
-Analysis of Security Protocols and Corresponding Cipher suites in ETSI M2M Standards
-Fast Velocity and Large Volume Data Processing in M2M Communications
-Design and Optimization of a Smartphone Gateway for Wearable Devices
-Charging Factors and Charging Architecture Study in M2M communications
-Performance Management of IoT/M2M Platforms
2016
-Charging Architecture in M2M Communications
-A Comparison and Evaluation of Different BLE Connection Methods for Wearable Devices
-Situation Awareness in a Smart Home Environment
-High Scalability for IoT/M2M Platforms
-Incorporating OMA LWM2M Gateway in M2M Standard Architecture
-Gesture-based Control in Smart Home
-OpenStack-based Highly Scalable IoT/M2M Platforms
2017
-OneM2M-based IoT Protocol Integration
-Preventing Misuse of Duplicate Certificates in IoT/M2M Systems
-Efficient Device Group Management in oneM2M
-Over-The-Air Provisioning for Wearable Devices via BLE and oneM2M
-Extending Scalability of IoT/M2M Platform with Fog Networking
-Extending IoT/M2M System Scalability by Network Slicing
-Ensuring IoT/M2M System Security under the Limitation of Constrained Gateways
-Situation Awareness in Smart Home based on Multiple User Activities Recognition
2018
-Enabling Direct Semantic Query in oneM2M
-IMU-Based Walking Workouts Recognition
-Distributed Artificial Intelligence enabled by Fog Networking
-OPC-UA Interworking with oneM2M
-Enhancing IoT/M2M System Scalability by Dynamic Network Slicing
-Identification and analysis of SDN/NFV charging factors
2019
-Enabling IoT/M2M System Scalability with Fog Computing
-Dynamic Fault Management in Service Function Chaining
-NFV-based Scalable IoT/M2M Platforms with Kubernetes
-Exploration of Charging Issues in 5G Networks
-Enabling Machine Learning across Heterogeneous Sensor Networks with Graph Autoencoders
-Distributed Semantic Reasoning enabled by Fog Computing
2020
-Enhancing Cloud-based IoT/M2M System Scalability by Dynamic Network Slicing
-Evaluating NFV-enabled Network Slicing for 5G Core
-NFV‐enabled Network Slicing for IoT
-Pricing 5G Network Slices based on NFV MANO
-Evaluation of 5G Core Slicing on User Plane Function
2021
-NFV-Enabled Hybrid Scalability for IoT Slices
-NFV-Enabled Vertical Scalability for IoT Slices
-Evaluating Dedicated Slices of Different Configurations in 5G Core
-Coordinated Management of 5G Core Slices by MANO and OSS/BSS
-Tackling IoT Scalability with 5G NFV-enabled Network Slicing
2022
-Enhancing 5G Core with Multi-Access Edge Computing
-5G Network Slice Scalability based on Management Data Analytics Function

The past funded projects include:
1. MOE - "Education Alliance for Advanced Networking Technologies 網通前瞻技術教學推動聯盟", 2012-2014.
2. Chunghwa Telecom - "Research & Design of interface and interoperation between Policy and Online Charging system", 2014.
3. Delta - "Cyber-Physical Security and Time Series Data in IoT/M2M Systems", 2014.
4. MOST - "Cloud and Big Data Computing Platforms for M2M Communications Systems", 2013-2016.
5. Chunghwa Telecom - "Smart Data Pricing for M2M Communications", 2015-2017.
6. Delta - "Device Management for IoT/M2M Cyber-Physical Systems", 2015.
7. MOST - "IoT/M2M Platform for Wearable Devices", 2014-2017.
8. MOST - "Massive Machine Communications in 5G", 2014-2017.
9. MOE - "Education Alliance for Advanced Mobile Broadband Technologies 行動寬頻尖端技術跨校教學聯盟", 2015-2017.
10. Chunghwa Telecom - "Real-Time Charging based on SDN/NFV", 2018
11. III - "Docker-based OpenFog IoT Technologies", 2017
12. III - "Research on Integrating IoT Platforms and Device Management", 2017
13. III - "Gateway Site Fog Computing", 2018
14. QNAP - "Authorization of IoT Devices” and “Security of Constrained Field Gateways", 2016-2017
15. Chunghwa Telecom - "Exploring Charging Issues and Innovative Services in 5G", 2019-2020.
16. MOST - "Scalability Research of IoT/M2M Platform", 2017-2020.
17. MOE - "MOOCs for 5G Mobile Broadband Education Alliance / 5G 行動寬頻跨校教學聯盟計畫", 2018-2020.
18. MOST - "Core Technologies and Application Developments for M2M Communication Systems", 2017-2020.
19. MOEA - "Promoting IoT and 5G innovations and services with SDN/NFV", 2018-2022.
20. MOE - "5G Mobile Broadband Education Alliance / 5G 行動寬頻跨校教學聯盟計畫", 2018-2021.
21. MOE - "Center for Open Intelligent Connectivity (OpInConnect)", 2018-2023.
22. MOE - "International Collaboratoin with Okinawa Open Laboratory", 2018-2023.
23. MOST - "Scalability Research of 5G Core Networks and Its Application to IoT", 2020-2021.
24. MOE - "Field Demonstration of 5G Campus Experiment Network Phase 1/ 5G校園實驗網示範場域第一期", 2019-2021.


The current funded projects include:
1. MOE - "Field Demonstration of 5G Campus Experiment Network Phase 2/ 5G校園實驗網示範場域第二期",2021-2022.
2. MOST - "Development of Open-source B5G/6G Core Networks",2021-2025.
3. MOST - "6G Networks that Support 3D Intelligent Communications / 支援 3D 智能通訊之 6G 網路",2022-2027.

Sorry that we have stopped accepting any new MS or PhD students.

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