The Choice Coordination Problem requiresn asynchronous processes to reach a common choice of one out ofk possible alternatives. Processes communicate viak shared variables. Up tot, t, of the processes may fail to oper...
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The Choice Coordination Problem requiresn asynchronous processes to reach a common choice of one out ofk possible alternatives. Processes communicate viak shared variables. Up tot, t, of the processes may fail to operate by suddenly quitting the protocol. Rabin (1982) presented lower and upper bounds for the extreme caset=n?1. We present deterministic and randomized algorithms for arbitraryt using an alphabet of sizeO(t 2). A semi-synchronous model is also studied. A reduction to a consensus problem proves the necessity to assume some powerful atomic shared-memory operations.
This article considers the problem of containment control in an adversarial environment, where some of the agents might be misbehaving (or faulty). Despite the influence of network misbehaviors, the normal followers a...
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This article considers the problem of containment control in an adversarial environment, where some of the agents might be misbehaving (or faulty). Despite the influence of network misbehaviors, the normal followers aim to move into the convex hull spanned by the normal leaders. Toward this goal, resilient containment control is investigated in this work. We propose secure protocols for both first-order and second-order systems, where each normal follower ignores the most extreme values in its neighborhood and modifies its state based on the remaining ones. Assuming that the number of malicious agents is locally upper bounded, sufficient conditions on the network topology are derived to guarantee the achievement of resilient containment. Numerical examples are also provided in the end to verify our theoretical results.
In this article, we investigate time-varying output formation tracking problems for heterogeneous multiagent systems in an adversarial environment, where both leaders and followers are vulnerable to cyber-attacks. Des...
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In this article, we investigate time-varying output formation tracking problems for heterogeneous multiagent systems in an adversarial environment, where both leaders and followers are vulnerable to cyber-attacks. Despite the presence of adversarial agents, the normal followers not suffering from cyber-attacks seek to achieve a desired formation configuration and track a safe trajectory generated by normal leaders' outputs simultaneously. To this end, a resilient time-varying output formation (RTVOF) tracking scheme is presented in this work. First, to counteract the effect of adversarial agents, a safety strategy is proposed for general linear heterogeneous systems, which is a synthesis of the mean-subsequence-reduced family algorithms and an attack detection procedure. Second, using the neighboring interaction, a resilient distributed observer and a local formation controller are designed for each normal follower to estimate the state and track the output of the safe formation reference. Then, it is proved that the heterogeneous multiagent system with multiple dynamic leaders and time-varying topologies can accomplish the RTVOF tracking if specific graph-theoretic properties and formation feasibility conditions are satisfied. Finally, simulation examples are given to demonstrate the effectiveness of obtained results.
Incorrect computer hardware behavior may corrupt intermediate computations in numerical algorithms, possibly resulting in incorrect answers. Prior work models misbehaving hardware by randomly flipping bits in memory. ...
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Incorrect computer hardware behavior may corrupt intermediate computations in numerical algorithms, possibly resulting in incorrect answers. Prior work models misbehaving hardware by randomly flipping bits in memory. We start by accepting this premise, and present an analytic model for the error introduced by a bit flip in an IEEE 754 floating-point number. We then relate this finding to the linear algebra concepts of normalization and matrix equilibration. In particular, we present a case study illustrating that normalizing both vector inputs of a dot product minimizes the probability of a single bit flip causing a large error in the dot product's result. Furthermore, the absolute error is either less than one or very large, which allows detection of large errors. Then, we apply this to the GMRES iterative solver. We count all possible errors that can be introduced through faults in arithmetic in the computationally intensive orthogonalization phase of GMRES, and show that when the matrix is equilibrated, the absolute error is bounded above by one. (C) 2016 Elsevier B.V. All rights reserved.
In this brief, we investigate the problem of resilient consensus in continuous-time second-order networks, where some nodes might be faulty or adversarial. Despite the existence of such malicious and unexpected behavi...
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In this brief, we investigate the problem of resilient consensus in continuous-time second-order networks, where some nodes might be faulty or adversarial. Despite the existence of such malicious and unexpected behaviors, the normal agents still aim to reach an agreement. Towards this end, a resilient impulsive algorithm is proposed, in which the signal transmission among agents occurs with aperiodic intervals. At each sampling time, the normal agent removes the most extreme values in the neighborhood and then derives its control signal with the remaining ones. We show the influence of the malicious nodes on the normal ones would be limited by this manner. Sufficient conditions related to the network topology and tolerable number of misbehaving nodes are finally established to achieve the resilient consensus.
This paper considers the multi-dimensional consensus in networked systems, where some of the agents might be misbehaving (or faulty). Despite the influence of these misbehaviors, the benign agents aim to reach an agre...
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This paper considers the multi-dimensional consensus in networked systems, where some of the agents might be misbehaving (or faulty). Despite the influence of these misbehaviors, the benign agents aim to reach an agreement while avoiding being seriously influenced by the faulty ones. To this end, this paper first considers a general class of consensus algorithms, where each benign agent computes an "auxiliary point" based on the received values and moves its state towards this point. Concerning this generic form, we present conditions for achieving resilient consensus and obtain a lower bound on the exponential convergence rate. Assuming that the number of malicious agents is upper bounded, two specific resilient consensus algorithms are further developed based on the obtained conditions. Particularly, the first solution, based on Helly's Theorem, achieves the consensus within the convex hull formed by the benign agents' initial states, where the auxiliary point can be efficiently computed through linear programming. On the other hand, the second algorithm serves as a "built-in" security guarantee for standard average consensus algorithms, in the sense that its performance coincides exactly with that of the standard ones in the absence of faulty nodes while also resisting the serious influence of the misbehaving ones in adversarial environment. Some numerical examples are provided in the end to verify the theoretical results. (C) 2022 Elsevier Ltd. All rights reserved.
In this paper, we consider the problem of output regulation in heterogeneous networked systems. In order to cooperatively achieve the global objective, each agent is required to share information in its neighborhood t...
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In this paper, we consider the problem of output regulation in heterogeneous networked systems. In order to cooperatively achieve the global objective, each agent is required to share information in its neighborhood through communication channels, which might be exposed to malicious cyber attacks. Past work shows that the performance of cooperative control can be seriously affected by network misbehaviors. Inspired by such security concerns, this paper considers the resilient cooperative output regulation (COR) in adversarial environment. Despite the presence of so-called Byzantine agents, the normally behaving ones still aim to achieve the goal of trajectory tracking or disturbance rejection. Towards this end, resilient observers with low computational cost are first developed based on a continuous-time resilient consensus protocol. When the number of Byzantine nodes is locally upper bounded and the network structure satisfies certain robustness properties, the designed observers enable each benign agent to exponentially track the exogenous signal. After that, decentralized controllers are proposed facilitating the achievement of resilient COR in the heterogeneous networks. A numerical example is finally given to illustrate the effectiveness of our approach. (C) 2021 Elsevier Ltd. All rights reserved.
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