797,570 research outputs found
Specification and Verification of Distributed Embedded Systems: A Traffic Intersection Product Family
Distributed embedded systems (DESs) are no longer the exception; they are the
rule in many application areas such as avionics, the automotive industry,
traffic systems, sensor networks, and medical devices. Formal DES specification
and verification is challenging due to state space explosion and the need to
support real-time features. This paper reports on an extensive industry-based
case study involving a DES product family for a pedestrian and car 4-way
traffic intersection in which autonomous devices communicate by asynchronous
message passing without a centralized controller. All the safety requirements
and a liveness requirement informally specified in the requirements document
have been formally verified using Real-Time Maude and its model checking
features.Comment: In Proceedings RTRTS 2010, arXiv:1009.398
Information Flow Structure in Large-Scale Product Development Organizational Networks
In recent years, understanding the structure and function of complex networks has become the foundation for explaining many different real- world complex social, information, biological and technological phenomena. Techniques from statistical physics have been successfully applied to the analysis of these networks, and have uncovered surprising statistical structural properties that have also been shown to have a major effect on their functionality, dynamics, robustness, and fragility. This paper examines, for the first time, the statistical properties of strategically important complex organizational information-based networks -- networks of people engaged in distributed product development -- and discusses the significance of these properties in providing insight into ways of improving the strategic and operational decision-making of the organization. We show that the patterns of information flows that are at the heart of large-scale product development networks have properties that are like those displayed by information, biological and technological networks. We believe that our new analysis methodology and empirical results are also relevant to other organizational information-based human or nonhuman networks.Large-scale product development, socio-technical systems, information systems, social networks, Innovation, complex engineering systems, distributed problem solving
Distributed Learning over Unreliable Networks
Most of today's distributed machine learning systems assume {\em reliable
networks}: whenever two machines exchange information (e.g., gradients or
models), the network should guarantee the delivery of the message. At the same
time, recent work exhibits the impressive tolerance of machine learning
algorithms to errors or noise arising from relaxed communication or
synchronization. In this paper, we connect these two trends, and consider the
following question: {\em Can we design machine learning systems that are
tolerant to network unreliability during training?} With this motivation, we
focus on a theoretical problem of independent interest---given a standard
distributed parameter server architecture, if every communication between the
worker and the server has a non-zero probability of being dropped, does
there exist an algorithm that still converges, and at what speed? The technical
contribution of this paper is a novel theoretical analysis proving that
distributed learning over unreliable network can achieve comparable convergence
rate to centralized or distributed learning over reliable networks. Further, we
prove that the influence of the packet drop rate diminishes with the growth of
the number of \textcolor{black}{parameter servers}. We map this theoretical
result onto a real-world scenario, training deep neural networks over an
unreliable network layer, and conduct network simulation to validate the system
improvement by allowing the networks to be unreliable
On the Convergence of the Holistic Analysis for EDF Distributed Systems
Dynamic scheduling techniques, and EDF (Earliest Deadline First) in particular, have demonstrated their ability to increase the schedulability of real time systems compared to fixed-priority scheduling. In distributed systems, the scheduling policies of the processing nodes tend to be the same as in stand-alone systems and, although few EDF networks exist, it is foreseen that dynamic scheduling will gradually develop into real-time networks. There are some response time analysis techniques for EDF scheduled distributed systems, mostly derived from the holistic analysis developed by Spuri. The convergence of the holistic analysis in context of EDF distributed systems with shared resources had not been studied until now. There is a circular dependency between tasksâ release jitter values, response times and preemption level ceilings of shared resources. In this paper we present an extension of Spuriâs algorithm and we demonstrate that its iterative formulas are non-decreasing, even in the presence of shared resources. This result enables us to assert that the new algorithm converges towards a solution for the response times of the tasks and messages in a distributed system
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