16,462 research outputs found
Minimizing Message Size in Stochastic Communication Patterns: Fast Self-Stabilizing Protocols with 3 bits
This paper considers the basic model of communication, in
which in each round, each agent extracts information from few randomly chosen
agents. We seek to identify the smallest amount of information revealed in each
interaction (message size) that nevertheless allows for efficient and robust
computations of fundamental information dissemination tasks. We focus on the
Majority Bit Dissemination problem that considers a population of agents,
with a designated subset of source agents. Each source agent holds an input bit
and each agent holds an output bit. The goal is to let all agents converge
their output bits on the most frequent input bit of the sources (the majority
bit). Note that the particular case of a single source agent corresponds to the
classical problem of Broadcast. We concentrate on the severe fault-tolerant
context of self-stabilization, in which a correct configuration must be reached
eventually, despite all agents starting the execution with arbitrary initial
states.
We first design a general compiler which can essentially transform any
self-stabilizing algorithm with a certain property that uses -bits
messages to one that uses only -bits messages, while paying only a
small penalty in the running time. By applying this compiler recursively we
then obtain a self-stabilizing Clock Synchronization protocol, in which agents
synchronize their clocks modulo some given integer , within rounds w.h.p., and using messages that contain bits only.
We then employ the new Clock Synchronization tool to obtain a
self-stabilizing Majority Bit Dissemination protocol which converges in time, w.h.p., on every initial configuration, provided that the
ratio of sources supporting the minority opinion is bounded away from half.
Moreover, this protocol also uses only 3 bits per interaction.Comment: 28 pages, 4 figure
Stabilizing Consensus with Many Opinions
We consider the following distributed consensus problem: Each node in a
complete communication network of size initially holds an \emph{opinion},
which is chosen arbitrarily from a finite set . The system must
converge toward a consensus state in which all, or almost all nodes, hold the
same opinion. Moreover, this opinion should be \emph{valid}, i.e., it should be
one among those initially present in the system. This condition should be met
even in the presence of an adaptive, malicious adversary who can modify the
opinions of a bounded number of nodes in every round.
We consider the \emph{3-majority dynamics}: At every round, every node pulls
the opinion from three random neighbors and sets his new opinion to the
majority one (ties are broken arbitrarily). Let be the number of valid
opinions. We show that, if , where is a
suitable positive constant, the 3-majority dynamics converges in time
polynomial in and with high probability even in the presence of an
adversary who can affect up to nodes at each round.
Previously, the convergence of the 3-majority protocol was known for
only, with an argument that is robust to adversarial errors. On
the other hand, no anonymous, uniform-gossip protocol that is robust to
adversarial errors was known for
Opinion Dynamics in Social Networks with Hostile Camps: Consensus vs. Polarization
Most of the distributed protocols for multi-agent consensus assume that the
agents are mutually cooperative and "trustful," and so the couplings among the
agents bring the values of their states closer. Opinion dynamics in social
groups, however, require beyond these conventional models due to ubiquitous
competition and distrust between some pairs of agents, which are usually
characterized by repulsive couplings and may lead to clustering of the
opinions. A simple yet insightful model of opinion dynamics with both
attractive and repulsive couplings was proposed recently by C. Altafini, who
examined first-order consensus algorithms over static signed graphs. This
protocol establishes modulus consensus, where the opinions become the same in
modulus but may differ in signs. In this paper, we extend the modulus consensus
model to the case where the network topology is an arbitrary time-varying
signed graph and prove reaching modulus consensus under mild sufficient
conditions of uniform connectivity of the graph. For cut-balanced graphs, not
only sufficient, but also necessary conditions for modulus consensus are given.Comment: scheduled for publication in IEEE Transactions on Automatic Control,
2016, vol. 61, no. 7 (accepted in August 2015
On stability and controllability of multi-agent linear systems
Recent advances in communication and computing have made the control and coordination of dynamic network agents to become an area of multidisciplinary research at the intersection of the theory of control systems, communication and linear algebra. The advances of the research in multi-agent systems are strongly supported by their critical applications in different areas as for example in consensus problem of communication networks, or formation control of mobile robots. Mainly, the consensus problem has been studied from the point of view of stability. Nevertheless, recently some researchers have started to analyze the controllability problems. The study of controllability is motivated by the fact that the architecture of communication network in engineering multi-agent systems is usually adjustable. Therefore, it is meaningful to analyze how to improve the controllability of a multi-agent system. In this work we analyze the stability and controllability of multiagent systems consisting of k + 1 agents with dynamics x¿i = Aixi + Biui, i = 0, 1, . . . , kPostprint (published version
Filtering and control for unreliable communication: The discrete-time case
Copyright © 2014 Guoliang Wei et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In the past decades, communication networks have been extensively employed in many practical control systems, such as manufacturing plants, aircraft, and spacecraft to transmit information and control signals between the system components. When a control loop is closed via a serial communication channel, a networked control system (NCS) is formed. NCSs have become very popular for their great advantages over traditional systems (e.g., low cost, reduced weight, and power requirements, etc.). Generally, it has been implicitly assumed that the communication between the system components is perfect; that is, the signals transmitted from the plant always arrive at the filter or controller without any information loss. Unfortunately, such an assumption is not always true. For example, a common feature of the NCSs is the presence of significant network-induced delays and data losses across the networks. Therefore, an emerging research topic that has recently drawn much attention is how to cope with the effect of network-induced phenomena due to the unreliability of the network communication. This special issue aims at bringing together the latest approaches to understand, filter, and control for discrete-time systems under unreliable communication. Potential topics include but are not limited to (a) multiobjective filtering or control, (b) network-induced phenomena, (c) stability analysis, (d) robustness and fragility, and (e) applications in real-world discrete-time systems
Preserving Stabilization while Practically Bounding State Space
Stabilization is a key dependability property for dealing with unanticipated
transient faults, as it guarantees that even in the presence of such faults,
the system will recover to states where it satisfies its specification. One of
the desirable attributes of stabilization is the use of bounded space for each
variable. In this paper, we present an algorithm that transforms a stabilizing
program that uses variables with unbounded domain into a stabilizing program
that uses bounded variables and (practically bounded) physical time. While
non-stabilizing programs (that do not handle transient faults) can deal with
unbounded variables by assigning large enough but bounded space, stabilizing
programs that need to deal with arbitrary transient faults cannot do the same
since a transient fault may corrupt the variable to its maximum value. We show
that our transformation algorithm is applicable to several problems including
logical clocks, vector clocks, mutual exclusion, leader election, diffusing
computations, Paxos based consensus, and so on. Moreover, our approach can also
be used to bound counters used in an earlier work by Katz and Perry for adding
stabilization to a non-stabilizing program. By combining our algorithm with
that earlier work by Katz and Perry, it would be possible to provide
stabilization for a rich class of problems, by assigning large enough but
bounded space for variables.Comment: Moved some content from the Appendix to the main paper, added some
details to the transformation algorithm and to its descriptio
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