Title
The Adversarial Noise Threshold for Distributed Protocols.
Abstract
We consider the problem of implementing distributed protocols, despite adversarial channel errors, on synchronous-messaging networks with arbitrary topology. In our first result we show that any n-party T-round protocol on an undirected communication network G can be compiled into a robust simulation protocol on a sparse (O(n) edges) subnetwork so that the simulation tolerates an adversarial error rate of Ω(1/n); the simulation has a round complexity of O([EQUATION]), where m is the number of edges in G. (So the simulation is work-preserving up to a log factor.) The adversary's error rate is within a constant factor of optimal. Given the error rate, the round complexity blowup is within a factor of O(k log n) of optimal, where k is the edge connectivity of G. We also determine that the maximum tolerable error rate on directed communication networks is Θ(1/s) where s is the number of edges in a minimum equivalent digraph. Next we investigate adversarial per-edge error rates, where the adversary is given an error budget on each edge of the network. We determine the limit for tolerable per-edge error rates on an arbitrary directed graph to within a factor of 2. However, the construction that approaches this limit has exponential round complexity, so we give another compiler, which transforms T-round protocols into O(mT)-round simulations, and prove that for polynomial-query black box compilers, the per-edge error rate tolerated by this last compiler is within a constant factor of optimal.
Year
DOI
Venue
2016
10.5555/2884435.2884453
SODA '16: Symposium on Discrete Algorithms Arlington Virginia January, 2016
Field
DocType
Volume
Black box (phreaking),Discrete mathematics,Binary logarithm,Exponential function,Computer science,Word error rate,Communication channel,Directed graph,Subnetwork,Digraph
Conference
abs/1412.8097
ISBN
Citations 
PageRank 
978-1-61197-433-1
2
0.37
References 
Authors
19
2
Name
Order
Citations
PageRank
William M. Hoza120.37
Leonard J. Schulman21328136.88