Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications

SimStore: Efficient Data Management for Network Propagation Simulation

Authors
Dacheng Qu, Lin Zhang, Zhao Cao
Corresponding Author
Dacheng Qu
Available Online January 2016.
DOI
https://doi.org/10.2991/icaita-16.2016.43How to use a DOI?
Keywords
social network; propagation; simulation; data management; compression
Abstract
Simulation is widely adopted in large scale network propagation analytics. Plenty of analytics scenarios require to retrieve, review the simulation status of a given time points or interval. Unfortunately, it is unaffordable to re-run the simulation due to the long running time and other costs in many cases. In this paper, we introduce a system (SimStore) to enable efficient storage and retrieval of simulation snapshots. We present a novel technique to compress a series of simulation snapshots in order to reduce the storage cost. Experimental results demonstrate the efficiency and effectiveness of the proposed methods.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
Series
Advances in Intelligent Systems Research
Publication Date
January 2016
ISBN
978-94-6252-162-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/icaita-16.2016.43How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Dacheng Qu
AU  - Lin Zhang
AU  - Zhao Cao
PY  - 2016/01
DA  - 2016/01
TI  - SimStore: Efficient Data Management for Network Propagation Simulation
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 168
EP  - 171
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.43
DO  - https://doi.org/10.2991/icaita-16.2016.43
ID  - Qu2016/01
ER  -