4,449 research outputs found

    An Optimal Self-Stabilizing Firing Squad

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    Consider a fully connected network where up to tt processes may crash, and all processes start in an arbitrary memory state. The self-stabilizing firing squad problem consists of eventually guaranteeing simultaneous response to an external input. This is modeled by requiring that the non-crashed processes "fire" simultaneously if some correct process received an external "GO" input, and that they only fire as a response to some process receiving such an input. This paper presents FireAlg, the first self-stabilizing firing squad algorithm. The FireAlg algorithm is optimal in two respects: (a) Once the algorithm is in a safe state, it fires in response to a GO input as fast as any other algorithm does, and (b) Starting from an arbitrary state, it converges to a safe state as fast as any other algorithm does.Comment: Shorter version to appear in SSS0

    Nothing Less than the Dignity of Man: Evolving Standards, Botched Executions and Utah\u27s Controversial Use of the Firing Squad

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    While outrage boils to the surface when Utah uses its firing squad option, there is little substantive legal development concerning the firing squad\u27s use. Few cases have challenged the firing squad\u27s constitutionality. This article discusses the legal and political implications of the firing squad. Using the Supreme Court\u27s everdeveloping Eighth Amendment jurisprudence as a guide, this article discusses whether the firing squad, both historically and in its present application, passes constitutional muster. Beyond those factors that trigger constitutional protection, this article discusses those elements of the firing squad\u27s use which define society\u27s humanity and demonstrate our dignity. In the end, those factors are framed and fashioned by each individual\u27s view of decency and dignity

    New Solutions to the Firing Squad Synchronization Problems for Neural and Hyperdag P Systems

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    We propose two uniform solutions to an open question: the Firing Squad Synchronization Problem (FSSP), for hyperdag and symmetric neural P systems, with anonymous cells. Our solutions take e_c+5 and 6e_c+7 steps, respectively, where e_c is the eccentricity of the commander cell of the dag or digraph underlying these P systems. The first and fast solution is based on a novel proposal, which dynamically extends P systems with mobile channels. The second solution is substantially longer, but is solely based on classical rules and static channels. In contrast to the previous solutions, which work for tree-based P systems, our solutions synchronize to any subset of the underlying digraph; and do not require membrane polarizations or conditional rules, but require states, as typically used in hyperdag and neural P systems

    Relating Knowledge and Coordinated Action: The Knowledge of Preconditions Principle

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    The Knowledge of Preconditions principle (KoP) is proposed as a widely applicable connection between knowledge and action in multi-agent systems. Roughly speaking, it asserts that if some condition is a necessary condition for performing a given action A, then knowing that this condition holds is also a necessary condition for performing A. Since the specifications of tasks often involve necessary conditions for actions, the KoP principle shows that such specifications induce knowledge preconditions for the actions. Distributed protocols or multi-agent plans that satisfy the specifications must ensure that this knowledge be attained, and that it is detected by the agents as a condition for action. The knowledge of preconditions principle is formalised in the runs and systems framework, and is proven to hold in a wide class of settings. Well-known connections between knowledge and coordinated action are extended and shown to derive directly from the KoP principle: a "common knowledge of preconditions" principle is established showing that common knowledge is a necessary condition for performing simultaneous actions, and a "nested knowledge of preconditions" principle is proven, showing that coordinating actions to be performed in linear temporal order requires a corresponding form of nested knowledge.Comment: In Proceedings TARK 2015, arXiv:1606.0729

    Dynamic neighbourhood cellular automata.

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    We propose a definition of cellular automaton in which each cell can change its neighbourhood during a computation. This is done locally by looking not farther than neighbours of neighbours and the number of links remains bounded by a constant throughout. We suggest that dynamic neighbourhood cellular automata can serve as a theoretical model in studying algorithmic and computational complexity issues of ubiquitous computations. We illustrate our approach by giving an optimal, logarithmic time solution of the Firing Squad Synchronization problem in this setting

    Distributed algorithms for hard real-time systems

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    viii+124hlm.;24c

    Achieving consensus in fault-tolerant distributed computer systems : protocols, lower bounds, and simulations

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1987.Vita.Bibliography: p. 145-149.by Brian A. Coan.Ph.D

    The Murray Ledger and Times, January 9, 1981

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    The Montclarion, March 05, 1971

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    Student Newspaper of Montclair State Collegehttps://digitalcommons.montclair.edu/montclarion/1146/thumbnail.jp

    Edge- and Node-Disjoint Paths in P Systems

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    In this paper, we continue our development of algorithms used for topological network discovery. We present native P system versions of two fundamental problems in graph theory: finding the maximum number of edge- and node-disjoint paths between a source node and target node. We start from the standard depth-first-search maximum flow algorithms, but our approach is totally distributed, when initially no structural information is available and each P system cell has to even learn its immediate neighbors. For the node-disjoint version, our P system rules are designed to enforce node weight capacities (of one), in addition to edge capacities (of one), which are not readily available in the standard network flow algorithms.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005
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