200,405 research outputs found

    Preliminary Design of the SAFE Platform

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    Safe is a clean-slate design for a secure host architecture. It integrates advances in programming languages, operating systems, and hardware and incorporates formal methods at every step. Though the project is still at an early stage, we have assembled a set of basic architectural choices that we believe will yield a high-assurance system. We sketch the current state of the design and discuss several of these choices

    Transparent Dynamic reconfiguration for CORBA

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    Distributed systems with high availability requirements have to support some form of dynamic reconfiguration. This means that they must provide the ability to be maintained or upgraded without being taken off-line. Building a distributed system that allows dynamic reconfiguration is very intrusive to the overall design of the system, and generally requires special skills from both the client and server side application developers. There is an opportunity to provide support for dynamic reconfiguration at the object middleware level of distributed systems, and create a dynamic reconfiguration transparency to application developers. We propose a Dynamic Reconfiguration Service for CORBA that allows the reconfiguration of a running system with maximum transparency for both client and server side developers. We describe the architecture, a prototype implementation, and some preliminary test result

    Automated Synthesis of SEU Tolerant Architectures from OO Descriptions

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    SEU faults are a well-known problem in aerospace environment but recently their relevance grew up also at ground level in commodity applications coupled, in this frame, with strong economic constraints in terms of costs reduction. On the other hand, latest hardware description languages and synthesis tools allow reducing the boundary between software and hardware domains making the high-level descriptions of hardware components very similar to software programs. Moving from these considerations, the present paper analyses the possibility of reusing Software Implemented Hardware Fault Tolerance (SIHFT) techniques, typically exploited in micro-processor based systems, to design SEU tolerant architectures. The main characteristics of SIHFT techniques have been examined as well as how they have to be modified to be compatible with the synthesis flow. A complete environment is provided to automate the design instrumentation using the proposed techniques, and to perform fault injection experiments both at behavioural and gate level. Preliminary results presented in this paper show the effectiveness of the approach in terms of reliability improvement and reduced design effort

    SPRK: A Low-Cost Stewart Platform For Motion Study In Surgical Robotics

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    To simulate body organ motion due to breathing, heart beats, or peristaltic movements, we designed a low-cost, miniaturized SPRK (Stewart Platform Research Kit) to translate and rotate phantom tissue. This platform is 20cm x 20cm x 10cm to fit in the workspace of a da Vinci Research Kit (DVRK) surgical robot and costs $250, two orders of magnitude less than a commercial Stewart platform. The platform has a range of motion of +/- 1.27 cm in translation along x, y, and z directions and has motion modes for sinusoidal motion and breathing-inspired motion. Modular platform mounts were also designed for pattern cutting and debridement experiments. The platform's positional controller has a time-constant of 0.2 seconds and the root-mean-square error is 1.22 mm, 1.07 mm, and 0.20 mm in x, y, and z directions respectively. All the details, CAD models, and control software for the platform is available at github.com/BerkeleyAutomation/sprk

    Towards Secure and Safe Appified Automated Vehicles

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    The advancement in Autonomous Vehicles (AVs) has created an enormous market for the development of self-driving functionalities,raising the question of how it will transform the traditional vehicle development process. One adventurous proposal is to open the AV platform to third-party developers, so that AV functionalities can be developed in a crowd-sourcing way, which could provide tangible benefits to both automakers and end users. Some pioneering companies in the automotive industry have made the move to open the platform so that developers are allowed to test their code on the road. Such openness, however, brings serious security and safety issues by allowing untrusted code to run on the vehicle. In this paper, we introduce the concept of an Appified AV platform that opens the development framework to third-party developers. To further address the safety challenges, we propose an enhanced appified AV design schema called AVGuard, which focuses primarily on mitigating the threats brought about by untrusted code, leveraging theory in the vehicle evaluation field, and conducting program analysis techniques in the cybersecurity area. Our study provides guidelines and suggested practice for the future design of open AV platforms

    Robustness and Adaptiveness Analysis of Future Fleets

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    Making decisions about the structure of a future military fleet is a challenging task. Several issues need to be considered such as the existence of multiple competing objectives and the complexity of the operating environment. A particular challenge is posed by the various types of uncertainty that the future might hold. It is uncertain what future events might be encountered; how fleet design decisions will influence and shape the future; and how present and future decision makers will act based on available information, their personal biases regarding the importance of different objectives, and their economic preferences. In order to assist strategic decision-making, an analysis of future fleet options needs to account for conditions in which these different classes of uncertainty are exposed. It is important to understand what assumptions a particular fleet is robust to, what the fleet can readily adapt to, and what conditions present clear risks to the fleet. We call this the analysis of a fleet's strategic positioning. This paper introduces how strategic positioning can be evaluated using computer simulations. Our main aim is to introduce a framework for capturing information that can be useful to a decision maker and for defining the concepts of robustness and adaptiveness in the context of future fleet design. We demonstrate our conceptual framework using simulation studies of an air transportation fleet. We capture uncertainty by employing an explorative scenario-based approach. Each scenario represents a sampling of different future conditions, different model assumptions, and different economic preferences. Proposed changes to a fleet are then analysed based on their influence on the fleet's robustness, adaptiveness, and risk to different scenarios

    Robustness and Adaptability Analysis of Future Military Air Transportation Fleets

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    Making decisions about the structure of a future military fleet is challenging. Several issues need to be considered, including multiple competing objectives and the complexity of the operating environment. A particular challenge is posed by the various types of uncertainty that the future holds. It is uncertain what future events might be encountered and how fleet design decisions will influence these events. In order to assist strategic decision-making, an analysis of future fleet options needs to account for conditions in which these different uncertainties are exposed. It is important to understand what assumptions a particular fleet is robust to, what the fleet can readily adapt to, and what conditions present risks to the fleet. We call this the analysis of a fleet’s strategic positioning. Our main aim is to introduce a framework that captures information useful to a decision maker and defines the concepts of robustness and adaptability in the context of future fleet design. We demonstrate our conceptual framework by simulating an air transportation fleet problem. We account for uncertainty by employing an explorative scenario-based approach. Each scenario represents a sampling of different future conditions and different model assumptions. Proposed changes to a fleet are then analysed based on their influence on the fleet’s robustness, adaptability, and risk to different scenarios
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