22,576 research outputs found
Self-stabilising Byzantine Clock Synchronisation is Almost as Easy as Consensus
We give fault-tolerant algorithms for establishing synchrony in distributed
systems in which each of the nodes has its own clock. Our algorithms
operate in a very strong fault model: we require self-stabilisation, i.e., the
initial state of the system may be arbitrary, and there can be up to
ongoing Byzantine faults, i.e., nodes that deviate from the protocol in an
arbitrary manner. Furthermore, we assume that the local clocks of the nodes may
progress at different speeds (clock drift) and communication has bounded delay.
In this model, we study the pulse synchronisation problem, where the task is to
guarantee that eventually all correct nodes generate well-separated local pulse
events (i.e., unlabelled logical clock ticks) in a synchronised manner.
Compared to prior work, we achieve exponential improvements in stabilisation
time and the number of communicated bits, and give the first sublinear-time
algorithm for the problem:
- In the deterministic setting, the state-of-the-art solutions stabilise in
time and have each node broadcast bits per time
unit. We exponentially reduce the number of bits broadcasted per time unit to
while retaining the same stabilisation time.
- In the randomised setting, the state-of-the-art solutions stabilise in time
and have each node broadcast bits per time unit. We
exponentially reduce the stabilisation time to while each node
broadcasts bits per time unit.
These results are obtained by means of a recursive approach reducing the
above task of self-stabilising pulse synchronisation in the bounded-delay model
to non-self-stabilising binary consensus in the synchronous model. In general,
our approach introduces at most logarithmic overheads in terms of stabilisation
time and broadcasted bits over the underlying consensus routine.Comment: 54 pages. To appear in JACM, preliminary version of this work has
appeared in DISC 201
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
Complexity of Multi-Value Byzantine Agreement
In this paper, we consider the problem of maximizing the throughput of
Byzantine agreement, given that the sum capacity of all links in between nodes
in the system is finite. We have proposed a highly efficient Byzantine
agreement algorithm on values of length l>1 bits. This algorithm uses error
detecting network codes to ensure that fault-free nodes will never disagree,
and routing scheme that is adaptive to the result of error detection. Our
algorithm has a bit complexity of n(n-1)l/(n-t), which leads to a linear cost
(O(n)) per bit agreed upon, and overcomes the quadratic lower bound
(Omega(n^2)) in the literature. Such linear per bit complexity has only been
achieved in the literature by allowing a positive probability of error. Our
algorithm achieves the linear per bit complexity while guaranteeing agreement
is achieved correctly even in the worst case. We also conjecture that our
algorithm can be used to achieve agreement throughput arbitrarily close to the
agreement capacity of a network, when the sum capacity is given
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