SSSP-Del: Fully Dynamic Distributed Algorithm for Single-Source Shortest Path

2025-08-19

AI Summary

Existing single-source shortest paths (SSSP) algorithms for large-scale dynamic graphs suffer from high query latency and fail to simultaneously support edge insertions/deletions, distributed execution, and low-latency responses. Method: This paper proposes the first vertex-centric, asynchronous, fully distributed dynamic SSSP algorithm, designed for shared-nothing architectures. It integrates a distributed stream processing framework, asynchronous message passing, and an incremental update mechanism to enable real-time handling of edge insertions and deletions. Contribution/Results: Extensive experiments on million-scale real-world and synthetic graphs demonstrate that our algorithm significantly reduces query latency and increases throughput compared to state-of-the-art baselines, while strictly guaranteeing solution stability and convergence.

Technology Category

• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Modern graphs are both large and dynamic, presenting significant challenges for fundamental queries, such as the Single-Source Shortest Path (SSSP) problem. Naively recomputing the SSSP tree after each topology change is prohibitively expensive, causing on-demand computation to suffer from high latency. Existing dynamic SSSP algorithms often cannot simultaneously handle both edge additions and deletions, operate in distributed memory, and provide low-latency query results. To address these challenges, this paper presents SSSP-Del, a new vertex-centric, asynchronous, and fully distributed algorithm for dynamic SSSP. Operating in a shared-nothing architecture, our algorithm processes streams of both edge insertions and deletions. We conduct a comprehensive evaluation on large real-world and synthetic graphs with millions of vertices, and provide a thorough analysis by evaluating result latency, solution stability, and throughput.

Problem

• Handles dynamic edge insertions and deletions in distributed graphs
• Reduces high latency in on-demand SSSP recomputation
• Operates asynchronously in shared-nothing distributed memory architecture

Innovation

• Fully dynamic distributed SSSP algorithm
• Handles both edge insertions and deletions
• Vertex-centric asynchronous shared-nothing architecture