A Parallel Platform for Fusion of Heterogeneous Stream Data

Shan Zhang, Jielong Xu, Sora Choi, Jian Tang, Pramod K. Varshney, Zhenhua Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2018 21st International Conference on Information Fusion, FUSION 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages588-594
Number of pages7
ISBN (Print)9780996452762
DOIs
StatePublished - Sep 5 2018
Event21st International Conference on Information Fusion, FUSION 2018 - Cambridge, United Kingdom
Duration: Jul 10 2018Jul 13 2018

Publication series

Name2018 21st International Conference on Information Fusion, FUSION 2018

Other

Other21st International Conference on Information Fusion, FUSION 2018
CountryUnited Kingdom
CityCambridge
Period7/10/187/13/18

Keywords

  • Parallel computing
  • copula theory
  • dependence modeling
  • heterogeneous sensor fusion

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Statistics, Probability and Uncertainty
  • Instrumentation

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  • Cite this

    Zhang, S., Xu, J., Choi, S., Tang, J., Varshney, P. K., & Chen, Z. (2018). A Parallel Platform for Fusion of Heterogeneous Stream Data. In 2018 21st International Conference on Information Fusion, FUSION 2018 (pp. 588-594). [8455777] (2018 21st International Conference on Information Fusion, FUSION 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ICIF.2018.8455777