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Energy-efficient Task Offloading and Sensing Decision for Edge Computing-enabled Vehicular Networks
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Title
Energy-efficient Task Offloading and Sensing Decision for Edge Computing-enabled Vehicular Networks
Alternative Title
엣지 컴퓨팅 기반 차량 네트워크에서의 에너지 효율적인 오프로딩 및 센싱 결정 기법
DGIST Authors
Hewon choJeongho KwakJemin Lee
Advisor
곽정호
Co-Advisor(s)
Jemin Lee
Issued Date
2023
Awarded Date
2023-08-01
Citation
Hewon cho. (2023). Energy-efficient Task Offloading and Sensing Decision for Edge Computing-enabled Vehicular Networks. doi: 10.22677/THESIS.200000687729
Type
Thesis
Description
차량 네트워크; 엣지 컴퓨팅; 최적화 문제; 차량 센서 네트워크; 센싱 결정 기법; 강화 학습; 정보의 최신성; Vehicular networks; convex optimization; edge computing; resource allocation; sensing decision
Table Of Contents
I. INTRODUCTION 1
1.1 Outline and Contributions 3
1.1.1 Chapter 2 3
1.1.2 Chapter 3 3
1.1.3 Chapter 4 4
II. Task Offloading for Edge Computing-enabled Vehicular Networks 6
2.1 Contribution of This Chapter 6
2.2 Notations 7
2.3 System Model 7
2.3.1 Network Model 7
2.3.2 Cooperative Offloading Model 8
2.4 Total Energy Minimization 15
2.4.1 Problem Formulation 15
2.4.2 Optimal Solution in Multi-Vehicle Case 17
2.4.3 Optimal Solution in Single-Vehicle Case 19
2.5 Extension to Online Scenario 24
2.5.1 Network Model and Cooperative Offloading Models in Online Scenario 25
2.5.2 Online Optimization 25
2.6 Numerical Results 27
2.6.1 Single-Vehicle Case 28
2.6.2 Multi-Vehicle Case 29
2.7 Conclusion 35
III. Sensing Decision for Edge Computing-enabled Vehicular Sensor Networks 36
3.1 Contribution of This Chapter 36
3.2 System Model 36
3.2.1 Network Model 36
3.2.2 Vehicular Sensing Model 37
3.2.3 Performance metric 40
3.3 reinforcement learning (RL)-Based Sensing Decision Algorithm 41
3.3.1 Markov decision process (MDP) Formulation 41
3.3.2 Proposed Network Architecture 43
3.4 Simulation Results 43
3.5 Conclusion 45
IV. Conclusions 46
References 47
URI
http://hdl.handle.net/20.500.11750/46409
http://dgist.dcollection.net/common/orgView/200000687729
DOI
10.22677/THESIS.200000687729
Degree
Doctor
Department
Department of Electrical Engineering and Computer Science
Publisher
DGIST
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