@inproceedings{72391dc5586742a8b25cd965fd814b46,
title = "A Parallel Platform for Fusion of Heterogeneous Stream Data",
abstract = "This paper presents a novel parallel platform, C-Storm (Copula-based Storm), for the computationally complex problem of fusion of heterogeneous data streams for inference. C-Storm is designed by marrying copula-based dependence modeling for highly accurate inference and a highly-regarded parallel computing platform Storm for fast stream data processing. C-Storm has the following desirable features: 1) C-Storm offers fast inference responses. 2) C-Storm provides high inference accuracies. 3) C-Storm is a general-purpose inference platform that can support data fusion applications. 4) C-Storm is easy to use and its users do not need to know deep knowledge of Storm or copula theory. We implemented C-Storm based on Apache Storm 1.0.2 and conducted extensive experiments using a typical data fusion application. Experimental results show that C-Storm offers a significant 4.7x speedup over a commonly used sequential baseline and higher degree of parallelism leads to better performance.",
keywords = "Parallel computing, copula theory, dependence modeling, heterogeneous sensor fusion",
author = "Shan Zhang and Jielong Xu and Sora Choi and Jian Tang and Varshney, {Pramod K.} and Zhenhua Chen",
note = "Publisher Copyright: {\textcopyright} 2018 ISIF; 21st International Conference on Information Fusion, FUSION 2018 ; Conference date: 10-07-2018 Through 13-07-2018",
year = "2018",
month = sep,
day = "5",
doi = "10.23919/ICIF.2018.8455777",
language = "English (US)",
isbn = "9780996452762",
series = "2018 21st International Conference on Information Fusion, FUSION 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "588--594",
booktitle = "2018 21st International Conference on Information Fusion, FUSION 2018",
}