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Control and Optimization Over Large-Scale Networks- [electronic resource]
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Control and Optimization Over Large-Scale Networks- [electronic resource]
자료유형  
 학위논문
Control Number  
0016933418
International Standard Book Number  
9798380384643
Dewey Decimal Classification Number  
621.3
Main Entry-Personal Name  
Lima Silva, Vinicius.
Publication, Distribution, etc. (Imprint  
[S.l.] : University of Pennsylvania., 2023
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2023
Physical Description  
1 online resource(119 p.)
General Note  
Source: Dissertations Abstracts International, Volume: 85-03, Section: A.
General Note  
Advisor: Ribeiro, Alejandro.
Dissertation Note  
Thesis (Ph.D.)--University of Pennsylvania, 2023.
Restrictions on Access Note  
This item must not be sold to any third party vendors.
Summary, Etc.  
요약The future of the Internet of Things (IoT) envisions very large networks of spatially distributed devices cooperating to solve common tasks in both industrial and urban environments. That vision fundamentally relies on the use of wireless communication across such networks to enable flexibility, mobility, and dynamic configurations. The use of wireless connectivity in place of traditional wired communication to handle communication between those components, however, adds particular challenges to the design of control, optimization and communication policies.Control systems, in particular, are traditionally designed under the assumption that communication between spatially distributed components is fast and reliable - which might not necessarily hold if the different components of the control system communicate over a wireless network. That is because wireless networks are characterized by rapidly changing transmission conditions and are further subject to packet losses as the transmission conditions in the channel deteriorate. That, in turn, implies that components of a wireless control system might have to operate under missing or outdated information. Communication policies for standard wireless networks, on the other hand, typically aim to optimize traditional communication metrics that might not necessarily optimize the performance of the specific application taking place over that network. Hence, in the first part of this work we present a constrained reinforcement learning framework for the joint design of control and communication policies that optimizes the performance of the control system while satisfying requirements on the usage of communication resources.As the scale of deployment of spatially distributed control systems grows, however, it becomes of paramount importance to design communication policies that not only minimize interference among concurrent transmissions and optimize the performance of the underlying application taking place over that network, but that are also scalable. In the second part of this dissertation we thus investigate the design of scalable resource allocation policies for wireless control systems. By incorporating the structure of the communication network into the parameterization used to represent the communication policy, we show that the proposed approach yields resource allocation policies that not only outperform hand-crafted solutions, but that can also be successfully transferred across networks of varying size.While the first two parts of this dissertation focus on the design of control and communication policies in wireless control systems, we study more general decision processes over networks in the third part of this work. In particular, we propose a meta-learning approach to solve distributed optimization problems and show that one can learn distributed optimization algorithms that can match or exceed the performance of hand-crafted ones.
Subject Added Entry-Topical Term  
Electrical engineering.
Subject Added Entry-Topical Term  
Systems science.
Subject Added Entry-Topical Term  
Communication.
Index Term-Uncontrolled  
Distributed optimization
Index Term-Uncontrolled  
Graph neural networks
Index Term-Uncontrolled  
Resource allocation
Index Term-Uncontrolled  
Wireless control systems
Index Term-Uncontrolled  
Internet of Things
Added Entry-Corporate Name  
University of Pennsylvania Electrical and Systems Engineering
Host Item Entry  
Dissertations Abstracts International. 85-03A.
Host Item Entry  
Dissertation Abstract International
Electronic Location and Access  
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Control Number  
joongbu:643242
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