Summary of Large Scale Graph Computing Models
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DOI: 10.23977/meet.2019.93736
Corresponding Author
Sheng Yang
ABSTRACT
Large-scale graph data is a research hotspot in the processing of big data and is generally used in traffic management, analysis of social network and semantic web, etc., resulting in the emergence of a variety of large-scale graph computing platforms. How to select a more suitable graph computing platform for different tasks has become one of the hot topics in the field of graph computing. The related knowledge of graph computing models is systematically reviewed in this paper. First of all, the concept of graph computing model is outlined, including the definition and characteristics of graph computing and the development of graph computing models. Then, three kinds of graph computing models are introduced. Finally, the development process of the graph computing models is summarized, and the future research direction is prospected.
KEYWORDS
Large-Scale Graph Computing, Graph Processing, Distributed Computing