Title: Understanding data flow graph for improving big data stream computing environments

Authors: Dawei Sun; Ge Fu; Xinran Liu; Dongfeng Ren

Addresses: Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China ' National Computer Network Emergency Response Technical Team, Coordination Center of China Beijing, 100029, China ' National Computer Network Emergency Response Technical Team, Coordination Center of China Beijing, 100029, China ' Network Security Department, Neusoft Corporation, Shenyang, 110179, China

Abstract: High throughput issue is one of the major obstacles for opening up the new big data stream computing era. A high throughput big data stream computing system is need, optimising the data flow graph is an important way to offer a high throughput computing environment in big data stream computing system. In this paper, the definition of data flow graph in big data stream computing is given and the properties of data flow graph are systematically analysed by referring to the stream computing theories. A series of optimisation strategies for data flow graph in big data stream computing environments are put forward, all those strategies will greatly improve the structure of data flow graph, and provide a high throughput environment for big data stream computing.

Keywords: data flow graph; big data; stream computing; high throughput computing; high real time; optimisation.

DOI: 10.1504/IJCSM.2014.066446

International Journal of Computing Science and Mathematics, 2014 Vol.5 No.4, pp.394 - 404

Received: 11 Jul 2014
Accepted: 21 Aug 2014
Published online: 31 Jan 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article