Title

Single-Source Shortest Path Tree for Big Dynamic Graphs

Abstract

Computing single-source shortest paths (SSSP) is one of the fundamental problems in graph theory. There are many applications of SSSP including finding routes in GPS systems and finding high centrality vertices for effective vaccination. In this paper, we focus on calculating SSSP on big dynamic graphs, which change with time. We propose a novel distributed computing approach, SSSPIncJoint, to update SSSP on big dynamic graphs using GraphX. Our approach considerably speeds up the recomputation of the SSSP tree by reducing the number of map-reduce operations required for implementing SSSP in the gather-apply- scatter programming model used by GraphX.

Meeting Name

2018 IEEE International Conference on Big Data, Big Data 2018 (2018: Dec. 10-13, Seattle, WA)

Department(s)

Computer Science

Research Center/Lab(s)

Intelligent Systems Center

Keywords and Phrases

Apache Spark; Big Dynamic Graphs; Map- Reduce; Single-Source Shortest Path (SSSP)

International Standard Book Number (ISBN)

978-153865035-6

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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