8,744 research outputs found

    Measurement Based Reconfigurations in Optical Ring Metro Networks

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    Single-hop wavelength division multiplexing (WDM) optical ring networks operating in packet mode are one of themost promising architectures for the design of innovative metropolitan network (metro) architectures. They permit a cost-effective design, with a good combination of optical and electronic technologies, while supporting features like restoration and reconfiguration that are essential in any metro scenario. In this article, we address the tunability requirements that lead to an effective resource usage and permit reconfiguration in optical WDM metros.We introduce reconfiguration algorithms that, on the basis of traffic measurements, adapt the network configuration to traffic demands to optimize performance. Using a specific network architecture as a reference case, the paper aims at the broader goal of showing which are the advantages fostered by innovative network designs exploiting the features of optical technologies

    Robust Control

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    The need to be tolerant to changes in the control systems or in the operational environment of systems subject to unknown disturbances has generated new control methods that are able to deal with the non-parametrized disturbances of systems, without adapting itself to the system uncertainty but rather providing stability in the presence of errors bound in a model. With this approach in mind and with the intention to exemplify robust control applications, this book includes selected chapters that describe models of H-infinity loop, robust stability and uncertainty, among others. Each robust control method and model discussed in this book is illustrated by a relevant example that serves as an overview of the theoretical and practical method in robust control

    Promoting the use of reliable rate based transport protocols: the Chameleon protocol

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    Rate-based congestion control, such as TFRC, has not been designed to enable reliability. Indeed, the birth of TFRC protocol has resulted from the need for a congestion-controlled transport protocol in order to carry multimedia traffic. However, certain applications still prefer the use of UDP in order to implement their own congestion control on top of it. The present contribution proposes to design and validate a reliable rate-based protocol based on the combined use of TFRC, SACK and an adapted flow control. We argue that rate-based congestion control is a perfect alternative to window-based congestion control as most of today applications need to interact with the transport layer and should not be only limited to unreliable services. In this paper, we detail the implementation of a reliable rate-based protocol named Chameleon and bring out to the networking community an ns-2 implementation for evaluation purpose

    Supervisory Wireless Control for Critical Industrial Applications

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    Robust and secure resource management for automotive cyber-physical systems

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    2022 Spring.Includes bibliographical references.Modern vehicles are examples of complex cyber-physical systems with tens to hundreds of interconnected Electronic Control Units (ECUs) that manage various vehicular subsystems. With the shift towards autonomous driving, emerging vehicles are being characterized by an increase in the number of hardware ECUs, greater complexity of applications (software), and more sophisticated in-vehicle networks. These advances have resulted in numerous challenges that impact the reliability, security, and real-time performance of these emerging automotive systems. Some of the challenges include coping with computation and communication uncertainties (e.g., jitter), developing robust control software, detecting cyber-attacks, ensuring data integrity, and enabling confidentiality during communication. However, solutions to overcome these challenges incur additional overhead, which can catastrophically delay the execution of real-time automotive tasks and message transfers. Hence, there is a need for a holistic approach to a system-level solution for resource management in automotive cyber-physical systems that enables robust and secure automotive system design while satisfying a diverse set of system-wide constraints. ECUs in vehicles today run a variety of automotive applications ranging from simple vehicle window control to highly complex Advanced Driver Assistance System (ADAS) applications. The aggressive attempts of automakers to make vehicles fully autonomous have increased the complexity and data rate requirements of applications and further led to the adoption of advanced artificial intelligence (AI) based techniques for improved perception and control. Additionally, modern vehicles are becoming increasingly connected with various external systems to realize more robust vehicle autonomy. These paradigm shifts have resulted in significant overheads in resource constrained ECUs and increased the complexity of the overall automotive system (including heterogeneous ECUs, network architectures, communication protocols, and applications), which has severe performance and safety implications on modern vehicles. The increased complexity of automotive systems introduces several computation and communication uncertainties in automotive subsystems that can cause delays in applications and messages, resulting in missed real-time deadlines. Missing deadlines for safety-critical automotive applications can be catastrophic, and this problem will be further aggravated in the case of future autonomous vehicles. Additionally, due to the harsh operating conditions (such as high temperatures, vibrations, and electromagnetic interference (EMI)) of automotive embedded systems, there is a significant risk to the integrity of the data that is exchanged between ECUs which can lead to faulty vehicle control. These challenges demand a more reliable design of automotive systems that is resilient to uncertainties and supports data integrity goals. Additionally, the increased connectivity of modern vehicles has made them highly vulnerable to various kinds of sophisticated security attacks. Hence, it is also vital to ensure the security of automotive systems, and it will become crucial as connected and autonomous vehicles become more ubiquitous. However, imposing security mechanisms on the resource constrained automotive systems can result in additional computation and communication overhead, potentially leading to further missed deadlines. Therefore, it is crucial to design techniques that incur very minimal overhead (lightweight) when trying to achieve the above-mentioned goals and ensure the real-time performance of the system. We address these issues by designing a holistic resource management framework called ROSETTA that enables robust and secure automotive cyber-physical system design while satisfying a diverse set of constraints related to reliability, security, real-time performance, and energy consumption. To achieve reliability goals, we have developed several techniques for reliability-aware scheduling and multi-level monitoring of signal integrity. To achieve security objectives, we have proposed a lightweight security framework that provides confidentiality and authenticity while meeting both security and real-time constraints. We have also introduced multiple deep learning based intrusion detection systems (IDS) to monitor and detect cyber-attacks in the in-vehicle network. Lastly, we have introduced novel techniques for jitter management and security management and deployed lightweight IDSs on resource constrained automotive ECUs while ensuring the real-time performance of the automotive systems

    Digital seismo-acoustic signal processing aboard a wireless sensor array for volcano monitoring

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    This work describes the design and implementation of a low cost wireless sensor array utilizing digital processing to conduct autonomous real-time seismo-acoustic signal analysis of earthquakes at actively erupting volcanoes. The array consists of (1) three sensor nodes, which comprise seismic and acoustic sensors, (2) a GPS-based time synchronization node, and (3) a base receiver node, which features a communication channel for long distance telemetry. These nodes are based on the Moteiv TMote Sky wireless platform. The signal analysis accomplishes Real-time Seismic-Amplitude Measurement (RSAM) and Seismic Spectral-Amplitude Measurement (SSAM) calculations, and the extraction of triggered arrival time, event duration, intensity, and a decimated version of the triggered events for both channels. These elements are fundamental descriptors of earthquake activity. The processed data from the sensor nodes are transmitted back to the central node, where additional processing may be performed. This final information can be transmitted periodically via low bandwidth telemetry options
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