SPATE: Compacting and exploring telco big data

Constantinos Costa; Georgios Chatzimilioudis; Demetrios Zeinalipour-Yazti; Mohamed F. Mokbel

doi:10.1109/ICDE.2017.203

SPATE: Compacting and exploring telco big data

Constantinos Costa, Georgios Chatzimilioudis, Demetrios Zeinalipour-Yazti, Mohamed F. Mokbel

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

In this demonstration paper, we present SPATE, an innovative telco big data exploration framework whose objectives are two-fold: (i) minimizing the storage space needed to incrementally retain data over time; and (ii) minimizing the response time for spatiotemporal data exploration queries over stored data. Our framework deploys lossless data compression to ingest streams of telco big data in the most compact manner retaining full resolution for data exploration tasks. We augment our storage structures with decaying principles that lead to the progressive loss of detail as information gets older. Our framework also includes visual and declarative interfaces for a variety of telco-specific data exploration tasks. We demonstrate SPATE in two modes: (i) Visual Mode, where attendees will be able to interactively explore synthetic telco traces we will provide; and (ii) SQL Mode, where attendees can submit custom SQL queries based on a provided schema.

Original language	English (US)
Title of host publication	Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017
Publisher	IEEE Computer Society
Pages	1419-1420
Number of pages	2
ISBN (Electronic)	9781509065431
DOIs	https://doi.org/10.1109/ICDE.2017.203
State	Published - May 16 2017
Event	33rd IEEE International Conference on Data Engineering, ICDE 2017 - San Diego, United States Duration: Apr 19 2017 → Apr 22 2017

Publication series

Name	Proceedings - International Conference on Data Engineering
ISSN (Print)	1084-4627

Other

Other	33rd IEEE International Conference on Data Engineering, ICDE 2017
Country/Territory	United States
City	San Diego
Period	4/19/17 → 4/22/17

Bibliographical note

Funding Information:
This work was supported in part by the University of Cyprus, an industrial sponsorship by MTN Cyprus and EU COST Action IC1304. The third author's research is supported by the Alexander von Humboldt-Foundation, Germany. The last author's research is supported by NSF grants IIS-0952977, IIS-1218168, IIS-1525953, CNS-1512877.

Publisher Copyright:
© 2017 IEEE.

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10.1109/ICDE.2017.203

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Costa, C., Chatzimilioudis, G., Zeinalipour-Yazti, D., & Mokbel, M. F. (2017). SPATE: Compacting and exploring telco big data. In Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017 (pp. 1419-1420). Article 7930100 (Proceedings - International Conference on Data Engineering). IEEE Computer Society. https://doi.org/10.1109/ICDE.2017.203

SPATE: Compacting and exploring telco big data. / Costa, Constantinos; Chatzimilioudis, Georgios; Zeinalipour-Yazti, Demetrios et al.
Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017. IEEE Computer Society, 2017. p. 1419-1420 7930100 (Proceedings - International Conference on Data Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Costa, C, Chatzimilioudis, G, Zeinalipour-Yazti, D & Mokbel, MF 2017, SPATE: Compacting and exploring telco big data. in Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017., 7930100, Proceedings - International Conference on Data Engineering, IEEE Computer Society, pp. 1419-1420, 33rd IEEE International Conference on Data Engineering, ICDE 2017, San Diego, United States, 4/19/17. https://doi.org/10.1109/ICDE.2017.203

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abstract = "In this demonstration paper, we present SPATE, an innovative telco big data exploration framework whose objectives are two-fold: (i) minimizing the storage space needed to incrementally retain data over time; and (ii) minimizing the response time for spatiotemporal data exploration queries over stored data. Our framework deploys lossless data compression to ingest streams of telco big data in the most compact manner retaining full resolution for data exploration tasks. We augment our storage structures with decaying principles that lead to the progressive loss of detail as information gets older. Our framework also includes visual and declarative interfaces for a variety of telco-specific data exploration tasks. We demonstrate SPATE in two modes: (i) Visual Mode, where attendees will be able to interactively explore synthetic telco traces we will provide; and (ii) SQL Mode, where attendees can submit custom SQL queries based on a provided schema.",

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note = "Funding Information: This work was supported in part by the University of Cyprus, an industrial sponsorship by MTN Cyprus and EU COST Action IC1304. The third author's research is supported by the Alexander von Humboldt-Foundation, Germany. The last author's research is supported by NSF grants IIS-0952977, IIS-1218168, IIS-1525953, CNS-1512877. Publisher Copyright: {\textcopyright} 2017 IEEE.; 33rd IEEE International Conference on Data Engineering, ICDE 2017 ; Conference date: 19-04-2017 Through 22-04-2017",

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SPATE: Compacting and exploring telco big data

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