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Cyber-physical system

About: Cyber-physical system is a research topic. Over the lifetime, 11096 publications have been published within this topic receiving 162489 citations. The topic is also known as: CPS.


Papers
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Journal ArticleDOI
TL;DR: This paper defines the independent batch scheduling in Computational Grid as a three-objective global optimization problem with makespan, flowtime and energy consumption as the main scheduling criteria minimized according to different security constraints, and develops six genetic-based single- and multi-population meta-heuristics for solving the considered optimization problem.

67 citations

Proceedings ArticleDOI
01 Dec 2014
TL;DR: This paper develops a mathematical approach for quantitatively assessing the probability of correctness of collected observations (about an evolving physical system) when the observations are reported by sources whose reliability is unknown, hence enabling their exploitation as state estimators in CPS feedback loops.
Abstract: Today's cyber-physical systems (CPS) increasingly operate in social spaces. Examples include transportation systems, disaster response systems, and the smart grid, where humans are the drivers, survivors, or users. Much information about the evolving system can be collected from humans in the loop, a practice that is often called crowd-sensing. Crowd-sensing has not traditionally been considered a CPS topic, largely due to the difficulty in rigorously assessing its reliability. This paper aims to change that status quo by developing a mathematical approach for quantitatively assessing the probability of correctness of collected observations (about an evolving physical system), when the observations are reported by sources whose reliability is unknown. The paper extends prior literature on state estimation from noisy inputs, that often assumed unreliable sources that fall into one or a small number of categories, each with the same (possibly unknown) background noise distribution. In contrast, in the case of crowd-sensing, not only do we assume that the error distribution is unknown but also that each (human) sensor has its own possibly different error distribution. Given the above assumptions, we rigorously estimate data reliability in crowd-sensing systems, hence enabling their exploitation as state estimators in CPS feedback loops. We first consider applications where state is described by a number of binary variables, then extend the approach trivially to multivalued variables. The approach also extends prior work that addressed the problem in the special case of systems whose state does not change over time. Evaluation results, using both simulation and a real-life case-study, demonstrate the accuracy of the approach.

67 citations

Journal ArticleDOI
TL;DR: This paper introduces a framework to assess the performance of manufacturing systems using hybrid simulation in real time based on a discrete and continuous model of manufacturing equipment integrated to run synchronously with the real plant floor operation.
Abstract: This paper introduces a framework to assess the performance of manufacturing systems using hybrid simulation in real time. Continuous and discrete variables of different machines are monitored to analyze performance using a virtual environment running synchronous to plant floor equipment as a reference. Data are extracted from machines using industrial Internet of Things solutions. Productivity and reliability of a physical system are compared in real time with data from a hybrid simulation. The simulation uses discrete-event systems to estimate performance metrics at a system level, and continuous dynamics at a machine level to monitor input and output variables. Simulation outputs are used as a reference to detect abnormal conditions based on deviations of real outputs in different stages of the process. This monitoring method is implemented in a fully automated manufacturing system testbed with robots and CNC machines. Machines are integrated on an Ethernet/IP control network using a programmable logic controller to coordinate actions and transfer data. Results demonstrated the capacity to perform real-time monitoring and capture performance errors within confidence intervals. Note to Practitioners —Estimating expected performance of a manufacturing system processing different parts across multiple machines is a complex problem due to the lack of closed-form equations. Existing solutions focus on monitoring stochastic variables such as production or failure rate, or machine dynamics in separate environments often running asynchronous to the real system. This paper addresses the problem of monitoring and assessing the performance of complex manufacturing systems in real time. The proposed framework uses a real-time hybrid simulation of manufacturing at a machine and system level. The hybrid approach is based on a discrete and continuous model of manufacturing equipment integrated to run synchronously with the real plant floor operation. Data from both the virtual and real environments are merged to assess performance. Deviations from expected values represent an error that can trigger a warning signal to production, maintenance, and/or manufacturing personnel at the plant regarding health and productivity of plant operations.

67 citations

Proceedings ArticleDOI
01 Aug 2016
TL;DR: This paper looks at digital trust technologies from the point of view of security and examines how they are making secure computing an attainable reality and revisits and analyses the Trusted Platform Module (TPM), Secure Elements (SE), Hypervisors and Virtualisation, Intel TXT, Trusted Execution Environments (TEE) and their application to the emerging domains of the IoT and CPS.
Abstract: Notions like security, trust, and privacy are crucial in the digital environment and in the future, with the advent of technologies like the Internet of Things (IoT) and Cyber-Physical Systems (CPS), their importance is only going to increase. Trust has different definitions, some situations rely on real-world relationships between entities while others depend on robust technologies to gain trust after deployment. In this paper we focus on these robust technologies, their evolution in past decades and their scope in the near future. The evolution of robust trust technologies has involved diverse approaches, as a consequence trust is defined, understood and ascertained differently across heterogeneous domains and technologies. In this paper we look at digital trust technologies from the point of view of security and examine how they are making secure computing an attainable reality. The paper also revisits and analyses the Trusted Platform Module (TPM), Secure Elements (SE), Hypervisors and Virtualisation, Intel TXT, Trusted Execution Environments (TEE) like GlobalPlatform TEE, Intel SGX, along with Host Card Emulation, and Encrypted Execution Environment (E3). In our analysis we focus on these technologies and their application to the emerging domains of the IoT and CPS.

67 citations

Journal ArticleDOI
TL;DR: An improved and secure authentication system free of correctness issues, to facilitate a key agreement between user and cloud server via trusted authority, based on the hardness assumption of Elliptic Curve Decisional Diffi-Hellman Problem.

67 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023831
20221,955
20211,283
20201,586
20191,576
20181,441