We analyze denial of service attacks for cyberphysical systems aimed at increasing age of incorrect information, a metric combining the description of staleness and incorrectness of the data exchanged. We utilize game...
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ISBN:
(纸本)9798350358513;9798350358520
We analyze denial of service attacks for cyberphysical systems aimed at increasing age of incorrect information, a metric combining the description of staleness and incorrectness of the data exchanged. We utilize game theory to study the strategic interaction between two players;the former is a legitimate transmitter that wants to deliver status updates about the cyber-physical system to a control unit, whereas the latter is an adversary that, when active, prevents this communication from happening so as to cause the information at the control unit to become wrong and obsolete over time. these players act in an adversarial setup with contrasting objectives, but also being constrained by a costs term for their activity. To this end, we develop an original model based on Markov chains to quantify the average age of incorrect information as the result of both players' actions. Our analysis explores the equilibria of the resulting interaction and, especially, quantifies the regions of the parameters for which the attacker is most harmful or, conversely, where a proper strategic reaction by the transmitter can keep the attack at bay. this enables a quantification of information security in cyber-physical systems that go beyond the simple need to oppose the attacker, rather identifying quantitative evaluations and precise countermeasures.
Quantum computing is in an era of limited resources. Current hardware lacks high fidelity gates, long coherence times, and the number of computational units required to perform meaningful computation. Contemporary qua...
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ISBN:
(纸本)9781450399166
Quantum computing is in an era of limited resources. Current hardware lacks high fidelity gates, long coherence times, and the number of computational units required to perform meaningful computation. Contemporary quantum devices typically use a binary system, where each qubit exists in a superposition of the | 0 > and | 1 > states. However, it is often possible to access the |2 > or even |3 > states in the same physical unit by manipulating the system in different ways. In this work, we consider automatically encoding two qubits into one four-state ququart via a compression scheme. We use quantum optimal control to design efficient proof-of-concept gates that fully replicate standard qubit computation on these encoded qubits. We extend qubit compilation schemes to efficiently route qubits on an arbitrary mixed-radix system consisting of both qubits and ququarts, reducing communication and minimizing excess circuit execution time introduced by longer-duration ququart gates. In conjunction withthese compilation strategies, we introduce several methods to find beneficial compressions, reducing circuit error due to computation and communication by up to 50%. these methods can increase the computational space available on a limited nearterm machine by up to 2x while maintaining circuit fidelity.
Distributed allocation of computing tasks over network resources is meant to decrease the cost of centralized allocation. However, existing analytical models consider practically indistinguishable resources, e.g., loc...
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ISBN:
(纸本)9783031707520;9783031707537
Distributed allocation of computing tasks over network resources is meant to decrease the cost of centralized allocation. However, existing analytical models consider practically indistinguishable resources, e.g., located in the data center. Withthe rise of edge computing, it becomes important to account for the impact of diverse latency values imposed by edge/cloud data center locations. In this paper, we study the optimization of computing task allocation considering boththe delays to reach edge/cloud data centers and the response times of servers. We explicitly evaluate the resulting performance under different scenarios. We show, through numerical analysis and real experiments, that differences in delays to reach data center locations cannot be neglected. We also study the price of anarchy of a distributed implementation of the computing task allocation and unveil important properties such as the price of anarchy being generally small, except when the system is overloaded, and its maximum can be computed with low complexity.
Caching function is a promising way to mitigate coldstart overhead in serverless computing. However, as caching also increases the resource cost significantly, how to make caching decisions is still challenging. We fi...
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ISBN:
(纸本)9798400703942
Caching function is a promising way to mitigate coldstart overhead in serverless computing. However, as caching also increases the resource cost significantly, how to make caching decisions is still challenging. We find that the prior "local cache control" designs are insufficient to achieve high cache efficiency due to the workload skewness across servers. In this paper, inspired by the idea of software defined network management, we propose Flame, an efficient cache system to manage cached functions with a "centralized cache control" design. By decoupling the cache control plane from local servers and setting up a separate centralized controller, Flame is able to make caching decisions considering a global viewof cluster status, enabling the optimized cache-hit ratio and resource efficiency. We evaluate Flame with real-world workloads and the evaluation results show that it can reduce the cache resource usage by 36% on average while improving the coldstart ratio by nearly 7x than the state-of-the-art method.
this paper aims to enhance Smith-predictor-based controlsystems (SPCSs) for multi-input multi-output (MIMO) time delay processes. Conventional SPCSs for MIMO processes have an array of classical feedback controller(s...
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Recent advances in AI/ML technologies have accelerated the development of various ML applications. One of the major trends in AI/ML application development is the increasing use of multiple ML models to support high-a...
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ISBN:
(纸本)9783031707520;9783031707537
Recent advances in AI/ML technologies have accelerated the development of various ML applications. One of the major trends in AI/ML application development is the increasing use of multiple ML models to support high-accuracy inference in a complex end-to-end ML serving. However, testing the right configuration of multiple ML models is expensive, and the application requirements for ML inferences are highly dependent on various factors like the quality of ML models, computing resource performance, and data quality. In this context, techniques and methods that help to emulate and analyze ML inference characteristics using queueing theory can reduce the development effort and cost for ML services encapsulating ML models but also the entire ML system. In this paper, we modeled and analyzed a queueing model for an ML systemthat uses ensemble learning as an inference method with a new rule and clarified the impacts of model design in ensemble learning on the system's performance. As a result, we demonstrate the usefulness of the analysis for understanding possible configurations and their efficiency in the ML systemthrough queueing analysis and simulation.
the Displacement probe is an important part of chromatic confocal systems, and its imaging capabilities directly affect the performance of the system. the optical structure of the probe is usually designed as a whole,...
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the proceedings contain 115 papers. the topics discussed include: traffic processing and fingerprint generation for smart home device event;Fingersound: a low-cost and deployable authentication system with fingertip s...
ISBN:
(纸本)9781665473156
the proceedings contain 115 papers. the topics discussed include: traffic processing and fingerprint generation for smart home device event;Fingersound: a low-cost and deployable authentication system with fingertip sliding sound;a distributed method to form UAV swarm based on moncular vision;time-frequency analysis-based transient harmonic feature extraction for load monitoring;hierarchical computing network collaboration architecture for industrial Internet of things;an improved spray and wait algorithm based on the node social tree;Melanlysis: a mobile deep learning approach for early detection of skin cancer;causal ordering in the presence of byzantine processes;Nuwa: a receiver-driven congestion control framework to achieve high-throughput and controlled delay over dynamic wireless networks;relationship between g-extra connectivity and G-restricted connectivity in networks;and tunable causal consistency: specification and implementation.
this article proposes the use of Kernel Ridge Regression (KRR) for modeling and anomaly detection in the temperature control of textile dyeing processes. the anomaly being considered is the inability to heat or cool t...
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Due the dual-frequency number-theoretic phase unwrapping approach is often used in high-speed FPP 3D measurements due to its small number of projected images. However, the traditional number-theoretic phase unwrapping...
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