905 research outputs found

    Dynamic FTSS in Asynchronous Systems: the Case of Unison

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    Distributed fault-tolerance can mask the effect of a limited number of permanent faults, while self-stabilization provides forward recovery after an arbitrary number of transient fault hit the system. FTSS protocols combine the best of both worlds since they are simultaneously fault-tolerant and self-stabilizing. To date, FTSS solutions either consider static (i.e. fixed point) tasks, or assume synchronous scheduling of the system components. In this paper, we present the first study of dynamic tasks in asynchronous systems, considering the unison problem as a benchmark. Unison can be seen as a local clock synchronization problem as neighbors must maintain digital clocks at most one time unit away from each other, and increment their own clock value infinitely often. We present many impossibility results for this difficult problem and propose a FTSS solution when the problem is solvable that exhibits optimal fault containment

    Bounding the Impact of Unbounded Attacks in Stabilization

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    Self-stabilization is a versatile approach to fault-tolerance since it permits a distributed system to recover from any transient fault that arbitrarily corrupts the contents of all memories in the system. Byzantine tolerance is an attractive feature of distributed systems that permits to cope with arbitrary malicious behaviors. Combining these two properties proved difficult: it is impossible to contain the spatial impact of Byzantine nodes in a self-stabilizing context for global tasks such as tree orientation and tree construction. We present and illustrate a new concept of Byzantine containment in stabilization. Our property, called Strong Stabilization enables to contain the impact of Byzantine nodes if they actually perform too many Byzantine actions. We derive impossibility results for strong stabilization and present strongly stabilizing protocols for tree orientation and tree construction that are optimal with respect to the number of Byzantine nodes that can be tolerated in a self-stabilizing context

    Necessary and sufficient conditions for 1-adaptivity

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    A Scalable Byzantine Grid

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    Modern networks assemble an ever growing number of nodes. However, it remains difficult to increase the number of channels per node, thus the maximal degree of the network may be bounded. This is typically the case in grid topology networks, where each node has at most four neighbors. In this paper, we address the following issue: if each node is likely to fail in an unpredictable manner, how can we preserve some global reliability guarantees when the number of nodes keeps increasing unboundedly ? To be more specific, we consider the problem or reliably broadcasting information on an asynchronous grid in the presence of Byzantine failures -- that is, some nodes may have an arbitrary and potentially malicious behavior. Our requirement is that a constant fraction of correct nodes remain able to achieve reliable communication. Existing solutions can only tolerate a fixed number of Byzantine failures if they adopt a worst-case placement scheme. Besides, if we assume a constant Byzantine ratio (each node has the same probability to be Byzantine), the probability to have a fatal placement approaches 1 when the number of nodes increases, and reliability guarantees collapse. In this paper, we propose the first broadcast protocol that overcomes these difficulties. First, the number of Byzantine failures that can be tolerated (if they adopt the worst-case placement) now increases with the number of nodes. Second, we are able to tolerate a constant Byzantine ratio, however large the grid may be. In other words, the grid becomes scalable. This result has important security applications in ultra-large networks, where each node has a given probability to misbehave.Comment: 17 page

    Dynamic FTSS in Asynchronous Systems: the Case of Unison

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    Distributed fault-tolerance can mask the effect of a limited number of permanent faults, while self-stabilization provides forward recovery after an arbitrary number of transient fault hit the system. FTSS protocols combine the best of both worlds since they are simultaneously fault-tolerant and self-stabilizing. To date, FTSS solutions either consider static (i.e. fixed point) tasks, or assume synchronous scheduling of the system components. In this paper, we present the first study of dynamic tasks in asynchronous systems, considering the unison problem as a benchmark. Unison can be seen as a local clock synchronization problem as neighbors must maintain digital clocks at most one time unit away from each other, and increment their own clock value infinitely often. We present many impossibility results for this difficult problem and propose a FTSS solution when the problem is solvable that exhibits optimal fault containment

    Distributed self-(star) minimum connected sensor cover algorithms

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    Wireless ad-hoc sensor networks are composed of a large number of tiny sensors with embedded microprocessors, that have very limited resources and yet must coordinate amongst themselves to form a connected network. Every sensor has a certain sensing radius, Rs, within which it is capable of covering a particular region by detecting or gathering certain data. Every sensor also has a communication radius, R c, within which it is capable of sending or receiving data; Given a query over a sensor network, the minimum connected sensor cover problem is to select a minimum, or nearly minimum, set of sensors, called a minimum connected sensor cover, such that the selected sensors cover the query region, and form a connected network amongst themselves. In this thesis, we use present three fully distributed, strictly localized, scalable, self-* solutions to the minimum connected sensor cover problem

    Asynchronous neighborhood task synchronization

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    Faults are likely to occur in distributed systems. The motivation for designing self-stabilizing system is to be able to automatically recover from a faulty state. As per Dijkstra\u27s definition, a system is self-stabilizing if it converges to a desired state from an arbitrary state in a finite number of steps. The paradigm of self-stabilization is considered to be the most unified approach to designing fault-tolerant systems. Any type of faults, e.g., transient, process crashes and restart, link failures and recoveries, and byzantine faults, can be handled by a self-stabilizing system; Many applications in distributed systems involve multiple phases. Solving these applications require some degree of synchronization of phases. In this thesis research, we introduce a new problem, called asynchronous neighborhood task synchronization ( NTS ). In this problem, processes execute infinite instances of tasks, where a task consists of a set of steps. There are several requirements for this problem. Simultaneous execution of steps by the neighbors is allowed only if the steps are different. Every neighborhood is synchronized in the sense that all neighboring processes execute the same instance of a task. Although the NTS problem is applicable in nonfaulty environments, it is more challenging to solve this problem considering various types of faults. In this research, we will present a self-stabilizing solution to the NTS problem. The proposed solution is space optimal, fault containing, fully localized, and fully distributed. One of the most desirable properties of our algorithm is that it works under any (including unfair) daemon. We will discuss various applications of the NTS problem

    An advanced performance analysis of self-stabilizing protocols: stabilization time with transient faults during convergence

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