Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item AGE OF INCORRECT INFORMATION: A NEW PERFORMANCE METRIC IN SEMANTIC COMMUNICATIONS(2023) Chen, Yutao; Ephremides, Anthony; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)With the increasing popularity of smart devices and the rapid development of networking and communication technologies, cyber-physical system applications have been widely deployed and are receiving increasing attention. Some examples of these systems include vehicle networks, where vehicles collect real-time external information through their on-board sensors and cameras to generate a reliable description of the surroundings; intelligent transportation systems, where real-time monitoring of road conditions and traffic congestion is essential; and natural or man-made disaster prevention and management, where real-time monitoring of omens and disaster propagation is crucial. A common feature of these systems is the high requirement for the timeliness of the acquired information, which has led to the development of optimization frameworks aimed at capturing information freshness. Age of Information (AoI) is a prime example, but it has the drawback of only considering information freshness and ignoring the importance of content. As a result, the Age of Incorrect Information (AoII) has been developed to capture both the freshness and content of information. In this dissertation, we study the fundamental nature and optimization of AoII in numerous systems. With the proliferation of smart devices, energy consumption has become a major concern. In the first part, we focus on the characteristics and performance of AoII under limited resources. In particular, we propose an efficient algorithm to obtain the AoII-optimal policy under resource-constrained conditions and compute the performance of the optimal policies. The massive connectivity of communication systems has made scheduling a hot research topic. In the second part, we analyze and optimize the performance of AoII in the scheduling problem. We present the Whittle's index policy for AoII, whose superior performance has been recognized in many other problems. However, it also has limitations. Therefore, we propose a new scheduling policy, the indexed priority policy, which has comparable performance to the Whittle's index policy but has broader applicability. With the unprecedented increase in the amount and types of data to be transmitted and the impact of external factors such as urban construction, data transmission will experience numerous uncertainties. Therefore, in the third part, we study the characteristics and optimization of AoII in an environment with random delays. Specifically, in the first half, we consider the case where the communication channel suffers from a random delay. In the second half, we build on the first half and consider the case where the transmitter has preemption capability. For both halves, we precisely compute the performance of some canonical policies and theoretically find the optimal policies, which lay the foundation for further generalization and application of AoII.Item The Fundamental Nature of Age of Incorrect Information(2020) Chen, Yutao; Ephremides, Anthony; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Age of Incorrect Information (AoII) is a newly introduced metric that captures not only the freshness of information but also the information content of the trans- mitted packets and the knowledge at the monitor. It overcomes the shortcomings of Age of Information (AoI) in many applications that involve the problem of remotely estimating an event in real-time. However, the fundamental nature of AoII has been elusive so far. This thesis considers a system in which a transmitter sends updates about a Markovian source to a remote monitor through an unreliable channel. By leveraging the notion of Markov Decision Process (MDP), it is shown that a simple ”always update” policy minimizes the AoII. The performances of ”always update” policy as well as a more general transmission policy - ”threshold update” policy are analyzed in this thesis. Lastly, numerical results that highlight the effects of the parameters on the performances of these two transmission policies are provided.