Almost Optimal Algorithms for Token Collision in Anonymous Networks

TL;DR

This paper introduces near optimal deterministic and randomized algorithms for detecting token collisions in anonymous distributed networks, achieving efficiency close to theoretical limits with minimal prior knowledge.

Contribution

It formalizes the token collision problem and provides near optimal algorithms with low round complexity, advancing distributed collision detection methods.

Findings

Deterministic algorithms run in O(D + kL/\u0064n) rounds.

Randomized algorithms also achieve near optimal efficiency.

Algorithms require limited prior knowledge about the network and tokens.

Abstract

In distributed systems, situations often arise where some nodes each holds a collection of tokens, and all nodes collectively need to determine whether all tokens are distinct. For example, if each token represents a logged-in user, the problem corresponds to checking whether there are duplicate logins. Similarly, if each token represents a data object or a timestamp, the problem corresponds to checking whether there are conflicting operations in distributed databases. In distributed computing theory, unique identifiers generation is also related to this problem: each node generates one token, which is its identifier, then a verification phase is needed to ensure all identifiers are unique. In this paper, we formalize and initiate the study of token collision. In this problem, a collection of $k$ tokens, each represented by some length-$L$ bit string, are distributed to $n$ nodes of an anonymous CONGEST network in an arbitrary manner. The nodes need to determine whether there are tokens with an identical value. We present near optimal deterministic algorithms for the token collision problem with $\tilde{O}(D+k\cdot L/\log{n})$ round complexity, where $D$ denotes the network diameter. Besides high efficiency, the prior knowledge required by our algorithms is also limited. For completeness, we further present a near optimal randomized algorithm for token collision.