A Self-Stabilizing Hashed Patricia Trie

TL;DR

This paper introduces a self-stabilizing protocol for a distributed hashed Patricia Trie, enabling efficient prefix searches in peer-to-peer networks with crash-prone peers, ensuring robustness and low overhead.

Contribution

It presents the first self-stabilizing protocol for a distributed hashed Patricia Trie, ensuring robustness and efficiency in dynamic peer-to-peer environments.

Findings

Longest prefix matching in O(log |x|) hash table reads

Low overhead in legal states

Asymptotically optimal memory usage of Θ(d) bits

Abstract

While a lot of research in distributed computing has covered solutions for self-stabilizing computing and topologies, there is far less work on self-stabilization for distributed data structures. Considering crashing peers in peer-to-peer networks, it should not be taken for granted that a distributed data structure remains intact. In this work, we present a self-stabilizing protocol for a distributed data structure called the hashed Patricia Trie (Kniesburges and Scheideler WALCOM'11) that enables efficient prefix search on a set of keys. The data structure has a wide area of applications including string matching problems while offering low overhead and efficient operations when embedded on top of a distributed hash table. Especially, longest prefix matching for $x$ can be done in $\mathcal{O}(\log |x|)$ hash table read accesses. We show how to maintain the structure in a self-stabilizing way. Our protocol assures low overhead in a legal state and a total (asymptotically optimal) memory demand of $\Theta(d)$ bits, where $d$ is the number of bits needed for storing all keys.