Optimal epidemic dissemination

TL;DR

This paper demonstrates that optimal epidemic rumor dissemination in fully connected networks can be achieved with minimal messages and rounds, contradicting previous lower bounds by leveraging a different sharing assumption.

Contribution

It introduces simple, address-oblivious algorithms that achieve asymptotically optimal dissemination with fewer messages by relaxing the rumor sharing assumption in the model.

Findings

Dissemination to all nodes in (ln n) rounds with n+o(n) messages.

Contradicts previous lower bounds by changing rumor sharing assumptions.

Algorithms are robust against adversarial and stochastic failures.

Abstract

We consider the problem of reliable epidemic dissemination of a rumor in a fully connected network of~$n$ processes using push and pull operations. We revisit the random phone call model and show that it is possible to disseminate a rumor to all processes with high probability using $\Theta(\ln n)$ rounds of communication and only $n+o(n)$ messages of size $b$, all of which are asymptotically optimal and achievable with pull and push-then-pull algorithms. This contradicts two highly-cited lower bounds of Karp et al. stating that any algorithm in the random phone call model running in $\mathcal{O}(\ln n)$ rounds with communication peers chosen uniformly at random requires at least $\omega(n)$ messages to disseminate a rumor with high probability, and that any address-oblivious algorithm needs $\Omega(n \ln \ln n)$ messages regardless of the number of communication rounds. The reason for this contradiction is that in the original work, processes do not have to share the rumor once the communication is established. However, it is implicitly assumed that they always do so in the proofs of their lower bounds, which, it turns out, is not optimal. Our algorithms are strikingly simple, address-oblivious, and robust against $\epsilon n$ adversarial failures and stochastic failures occurring with probability $\delta$ for any $0 \leq \{\epsilon,\delta\} < 1$. Furthermore, they can handle multiple rumors of size $b \in \omega(\ln n \ln \ln n)$ with $nb + o(nb)$ bits of communication per rumor.