Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)

A Stream Computing Method for Railway Distribution Network Monitoring Information Based on Storm

Authors
Zhijian QU, Qunfeng WANG, Xiang PENG, Ruilin ZHOU
Corresponding Author
Zhijian QU
Available Online July 2017.
DOI
https://doi.org/10.2991/eia-17.2017.84How to use a DOI?
Keywords
intelligent dispatching; stream computing; publish subscribe; Storm
Abstract

Aiming at the problem of rapid processing of real - time data in intelligent dispatching, a new method for calculating the information flow of distribution network monitoring is proposed. Access the distribution network monitoring data by publishing subscriptions, combining the topology parallel model of flow calculation, comprehensive use of multi - theme partition message caching technology, to achieve low-latency and high-throughput processing of distribution network monitoring information[1-3]. The method can obtain hundreds of millisecond monitoring data processing delay, and it has practical value in research to improve low-latency distribution network dispatch system.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
Series
Advances in Intelligent Systems Research
Publication Date
July 2017
ISBN
10.2991/eia-17.2017.84
ISSN
1951-6851
DOI
https://doi.org/10.2991/eia-17.2017.84How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhijian QU
AU  - Qunfeng WANG
AU  - Xiang PENG
AU  - Ruilin ZHOU
PY  - 2017/07
DA  - 2017/07
TI  - A Stream Computing Method for Railway Distribution Network Monitoring Information Based on Storm
BT  - Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
PB  - Atlantis Press
SP  - 393
EP  - 395
SN  - 1951-6851
UR  - https://doi.org/10.2991/eia-17.2017.84
DO  - https://doi.org/10.2991/eia-17.2017.84
ID  - QU2017/07
ER  -