Electrical and Computer Engineering ETDs
Publication Date
Fall 12-13-2024
Abstract
Cyber-Physical Systems (CPSs) integrate computation, networking, and physical processes, while Cyber-Physical Networks (CPNs) enable communication and coordination among components. With advances in IoT and smart devices, CPSs are increasingly vital for applications such as smart grids, industrial automation, and autonomous vehicles. This dissertation explores decision making and performance optimization in Distributed Cyber-Physical Networks (DCPNs), focusing on efficiency, reliability, decentralization, and security. Using network economic theories (e.g., game theory, contract theory) and machine learning (e.g., Reinforcement Learning, Federated Learning), it addresses key problems: 1) a cost-effective positioning system with Reconfigurable Intelligent Surfaces (RISs) and RL, 2) energy-efficient task offloading in Multi-access Edge Computing (MEC) using RISs and contract theory, 3) UAV-based task offloading for public safety agents using RL and contract theory, and 4) a secure blockchain-based V2V energy-trading protocol using PKI and Stackelberg game. Extensive simulations validate the proposed models, advancing both theoretical and practical solutions for DCPNs.
Keywords
Cyber-physical network, Performance optimization, Decision making, Energy trading, Game theory, Machine learning
Document Type
Dissertation
Language
English
Degree Name
Computer Engineering
Level of Degree
Doctoral
Department Name
Electrical and Computer Engineering
First Committee Member (Chair)
Eirini Eleni Tsiropoulou
Second Committee Member
James Plusquellic
Third Committee Member
Ramiro Jordan
Fourth Committee Member
Symeon Papavassiliou
Recommended Citation
Hossain, Md Sahabul. "Decision Making and Performance Optimization in Distributed Cyber Physical Networks." (2024). https://digitalrepository.unm.edu/ece_etds/688
