SPATE: Compacting and exploring telco big data

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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017
PublisherIEEE Computer Society
Pages1419-1420
Number of pages2
ISBN (Electronic)9781509065431
DOIs
StatePublished - May 16 2017
Event33rd IEEE International Conference on Data Engineering, ICDE 2017 - San Diego, United States
Duration: Apr 19 2017Apr 22 2017

Publication series

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

Other

Other33rd IEEE International Conference on Data Engineering, ICDE 2017
Country/TerritoryUnited States
CitySan Diego
Period4/19/174/22/17

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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