Distributed Computing with Channel Noise
This addresses the challenge of secure distributed computing for users in noisy or adversarial network environments, presenting a novel algorithmic solution.
The paper tackles the problem of simulating a distributed protocol in the presence of an adversary that maliciously flips bits on communication channels, showing that it is possible to create a robust version that fails with probability at most δ and sends Õ(L + T) bits, with improvements when the average message size α is not constant, achieving O(L+T) bits if α is Ω(log(nL/δ)).
A group of $n$ users want to run a distributed protocol $π$ over a network where communication occurs via private point-to-point channels. Unfortunately, an adversary, who knows $π$, is able to maliciously flip bits on the channels. Can we efficiently simulate $π$ in the presence of such an adversary? We show that this is possible, even when $L$, the number of bits sent in $π$, and $T$, the number of bits flipped by the adversary are not known in advance. In particular, we show how to create a robust version of $π$ that 1) fails with probability at most $δ$, for any $δ>0$; and 2) sends $\tilde{O}(L + T)$ bits, where the $\tilde{O}$ notation hides a $\log (nL/ δ)$ term multiplying $L$. Additionally, we show how to improve this result when the average message size $α$ is not constant. In particular, we give an algorithm that sends $O( L (1 + (1/α) \log (n L/δ) + T)$ bits. This algorithm is adaptive in that it does not require a priori knowledge of $α$. We note that if $α$ is $Ω\left( \log (n L/δ) \right)$, then this improved algorithm sends only $O(L+T)$ bits, and is therefore within a constant factor of optimal.