Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

GOFS: A Model for Solving Overload on Distributed Stream Calculating System

Authors
Kailin Tang
Corresponding Author
Kailin Tang
Available Online May 2018.
DOI
10.2991/ncce-18.2018.150How to use a DOI?
Keywords
GOFS; calculating system; overloaded; dynamic resource.
Abstract

Nowadays, distributed Stream calculating is a leading technology for analyzing and managing massive streaming data. When distributed Stream calculating system working, because of data volume and distribution in the input streams often change over time, the system may be overloaded. While overload can cause the system to crash. This paper presents GOFS, a model for solving overload on distributed stream calculating system. GOFS is based on dynamic resource scheduling and load shedding. Extensive experiments are conducted to evaluate the performance and effectiveness of GOFS.

Copyright
© 2018, 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 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
Series
Advances in Intelligent Systems Research
Publication Date
May 2018
ISBN
10.2991/ncce-18.2018.150
ISSN
1951-6851
DOI
10.2991/ncce-18.2018.150How to use a DOI?
Copyright
© 2018, 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  - Kailin Tang
PY  - 2018/05
DA  - 2018/05
TI  - GOFS: A Model for Solving Overload on Distributed Stream Calculating System
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 899
EP  - 902
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.150
DO  - 10.2991/ncce-18.2018.150
ID  - Tang2018/05
ER  -