Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	364895	Edge Computing and Intelligent Network Systems	1	3.0	3	★	Cheng-Yun Ho	GCSIE	17	0

Course Plan：

Instructor	Cheng-Yun Ho　Office Hours
Email	cyho@ntut.edu.tw
Last Updated	2026-06-06 12:59:31
Course Objective	本課程探討邊緣運算（Edge Computing）於現代分散式系統與智慧網路中的核心角色，強調從傳統雲端架構轉向「雲–邊–端協同（Cloud–Edge–Device Continuum）」之設計思維。課程內容涵蓋邊緣架構設計、資源配置與任務卸載（offloading）、邊緣人工智慧（Edge AI）、以及與5G/6G通訊系統之整合。此外，課程將深入探討低延遲應用（如智慧製造、AR/VR、自駕車）、邊緣資料分析、隱私保護與安全機制，並介紹容器化（containerization）、微服務（microservices）與邊緣原生（edge-native）系統設計。透過論文文獻研讀與專題實作，使學生具備設計與實現新世代邊緣智慧系統之能力。 This course explores the principles and emerging trends of edge computing in modern distributed and intelligent network systems. It focuses on the paradigm shift from centralized cloud computing to the Cloud–Edge–Device continuum, enabling low-latency, real-time, and context-aware services. Topics include edge architecture design, resource management, task offloading, edge AI, federated learning, and integration with 5G/6G networks. The course also covers edge analytics, security and privacy, and cloud-native technologies such as containers and microservices. Students will engage in paper reading and hands-on projects to develop advanced edge-enabled intelligent systems.
Course Schedule	Week 1 Introduction to Edge Computing and Emerging Applications Week 2 Cloud–Edge–Device Continuum Architecture Week 3 Containerization and Edge Computing Platforms Week 4 Resource Management and Service Deployment Week 5 SDN and NFV Technologies Week 6 Intelligent Networking and Traffic Management Week 7 Research Topics, Literature Search, and Paper Reading Week 8 Project Proposal Presentation Week 9 Edge AI and Model Deployment Week 10 Task Offloading and Computation Migration Week 11 Federated Learning and Distributed Intelligence Week 12 Security and Privacy in Edge Computing Week 13 5G/6G and Multi-access Edge Computing (MEC) Week 14 Emerging Trends in Edge Intelligence and Paper Review Week 15 Final Project Presentation and Research Report (I) Week 16 Final Project Presentation and Research Report (II) Week 17 (Flexible Learning) Independent Paper Study and Literature Review Report Week 18 (Flexible Learning) Research Presentation, Reflection, and Future Research Planning
Evaluation and grading policy	1. Class Participation and Discussion: 10% 2. Project Proposal Presentation: 20% 3. Literature Review and Paper Analysis Report: 20% 4. Project Implementation and System Development: 30% 5. Final Project Presentation and Research Report: 20%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No Class material: Handout
The access to curricular consultation	Office hours or by appointment. Office location: Hung-Yu Research Tech Building Room 1533. Announce will show on i-School or Zuvio
Expanding teaching and resources	● 參與式創新教學 (Participatory & Innovative Teaching) 強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。 Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification. ● 混成學習 (Blended Learning) 課程結合實體授課與線上學習（同步視訊／非同步活動）。 Combines face-to-face instruction with online learning (including synchronous video sessions or asynchronous activities). ● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
The course corresponds to the SDGs	SDG4：優質教育（Quality Education）
Does the course incorporate AI	● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process） ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
Note	Flexible Learning 1. Category Independent Learning and Research Paper Study 2. Content Week 17: Independent study of selected research papers Week 18: Research presentation preparation and reflection 3. Hours Total 6 hours (3 hours per week) 4. Learning Outcomes One Independent Learning Report including: (1) Summary of 1–2 research papers (2) Brief literature comparison and analysis (3) Personal reflection and future research direction 5. Assessment Accounts for 5% of final grade, evaluated based on the quality of the Independent Learning Report.