Large-scale Graph Analysis: System, Algorithm and Optimization (1st ed. 2020) (Big Data Management)

By: Yingxia Shao and Bin Cui and Lei Chen

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Synopsis: 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.

Book Quality:: Publisher Quality
ISBN-13:: 9789811539282
Related ISBNs:: 9789811539275
Publisher:: Springer Singapore, Singapore
Date of Addition:: 08/02/20
Copyrighted By:: Springer
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Science, Computers and Internet, Business and Finance
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.