Large-Scale Graph Analysis: System, Algorithm and Optimization

By Lei Chen, Bin Cui, Yingxia Shao

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms - the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms.

This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.

• Format: Paperback
• Language: English
• ISBN: 9811539308
• ISBN13: 9789811539305
• Release Date: July 2021
• Publisher: Springer
• Length: 146 Pages
• Weight: 0.52 lbs.
• Dimensions: 0.3" x 6.1" x 9.2"