Master of Science in Engineering, University of Akron, 2022, Electrical Engineering

A decentralized framework for network optimization is presented for wireless sensing nodes. The wireless sensing nodes use a dynamic programming algorithm to choose optimal routes for data transmission from any network node to a specialized ‘gateway' node that provides access to the wider internet. The dynamic programming algorithm is a variation of the Bellman-Ford algorithm and allows for the wireless sensing nodes to make decisions based on locally available network information, resulting in a decentralized routing algorithm. Routing decisions depend on the cost it takes to communicate from a node to a gateway, either directly or indirectly, using neighboring nodes as relay points. Nodes constantly share information with neighbors and when something effects the cost of a path, such as a node failure or the discovery of a less costly route, all nodes upstream along the existing path are made aware and re-route accordingly. A sample network is used to illustrate and verify the functionality of the proposed algorithm. The network and node decisions are simulated to show the evolution of the network routing decisions, and the simulation consistently shows the network converging to an optimal configuration. The speed of convergence depends on the order in which the nodes are assumed to attempt to establish and optimize their connections.

Committee: Robert Veillette (Advisor); Jose Alexis De Abreu Garcia (Committee Member); Nghi Tran (Committee Member) Subjects: Applied Mathematics; Computer Engineering; Computer Science; Electrical Engineering; Engineering

Master of Science, The Ohio State University, 2023, Computer Science and Engineering

Blockchain is a decentralized, peer-to-peer (P2P) network that is becoming more popular because of its many benefits, such as reliability, scalability, and privacy over centralized networks. This technology gained traction in cryptocurrencies originally then it spread into the industry. But centralized networks still outperform decentralized networks in broadcast speed. Blockchain transactions have volatile latencies ranging from minutes to months, depending on the network traffic, while centralized transactions take milliseconds to complete. As network transactions increase, blockchain messages will reach their destinations slower. In this paper, we attempt to solve this problem in a decentralized manner by optimizing the P2P network's topology and making each unconnected node choose its best local connections. In an environment where network nodes trust each other and cannot connect to malicious nodes, these networks can decrease latency by creating node embeddings and predicting a node's best local connections with our AI model that consists of Multi-armed Bandits, Graph Convolutional Neural Networks, and Reinforcement Learning.

Committee: Shaileshh Venkatakrishnan (Advisor); Feng Qin (Committee Chair) Subjects: Artificial Intelligence; Computer Science

Doctor of Philosophy, The Ohio State University, 2017, Electrical and Computer Engineering

The power system is provisioned to evolve into a smart grid that is greener, safer, and more efficient. DC microgrid, a new form of distribution system and an emerging electrical network on ships/airplanes/electronic devices, has risen to prominence as an important building block of the future grid and many other applications. With proper operation and coordination, DC microgrids can exploit the flexibility in generation as well as consumption units, which have been standing unresponsive for decades, to approach a more robust and efficient grid such that every component in a power grid can reach its full potential to vibrantly participate in grid services. This dissertation presents systematic approaches to solve DC microgrid control and optimization problems that are usually marked by challenges like uncertainty, nonlinearity, tractability, and structural constraint issues. First, it is well known that when a DC microgrid is operated in island mode, the stability critical power balance is shadowed by uncertain and volatile generation and consumption. We propose a robust stability framework containing a set of sufficient conditions to provide provable stability guarantee for such systems. We then further investigate into robust control design to improve the performance of the system. In view of the physical communication structures that commonly exist in a microgrid, decentralized/distributed controllers are recognized to be more applicable in practice for their limited reliance on information transmissions. Nevertheless, with the communication structural constraints, the decentralized/distributed control design problem is NP-hard in general, and an ill-designed controller may as well render an originally operative system unstable. We propose an algorithm to design a structurally constrained controller in such a way that it can guarantee a design direction with provable improving performance. Second, for DC microgrids that are in grid-connected mode, the (open full item for complete abstract)

Committee: Wei Zhang (Advisor); Giorgio Rizzoni (Advisor); Antonio Conejo (Committee Member); Mahesh Illindala (Committee Member); Andrej Rotter (Other) Subjects: Electrical Engineering; Energy; Engineering; Operations Research