skip to main content
10.1145/2002259.2002301acmconferencesArticle/Chapter ViewAbstractPublication PagesdebsConference Proceedingsconference-collections
research-article

A paradigm comparison for collecting TV channel statistics from high-volume channel zap events

Published: 11 July 2011 Publication History

Abstract

The current approach used to obtain official television channel statistics is based on polls combined with specialized reporting hardware. These are deployed only on a small scale and batch processed every 24~hours. With the enhanced capabilities of present-day IPTV set-top-boxes, network operators can track channel popularity and usage patterns with a degree of precision and sophistication not possible with existing methods. One such network operator, Altibox, is the largest provider of IPTV in Norway with a deployment of over 320,000 set top-boxes. By tapping into the high-volume stream of channel zap events sent from these set-top boxes, very accurate viewership can be obtained and presented in near real-time.
In this paper, we examine two programming paradigms for implementing applications to compute viewership based on channel zap events. One based on a general-purpose programming language (Java) and the other based on a highly specialized event stream processing language (EPL). An important characteristic of this application is stateful event processing. We are interested in exploring the trade-offs between these two implementations, to determine their suitability for such applications. Specifically, we are interested in the performance trade-off and the program complexity of each implementation.
Our results show that a pure Java implementation has a significant edge over EPL in terms of performance. Although, our numbers cannot be used to draw a general conclusion, it seems indicative that an event stream processing engine would suffer more than a general-purpose language as query complexity grows. We conjecture that this is because it is easier to construct custom data structures for the specific problem in a general-purpose language like Java. In terms of program complexity, EPL has a slight edge in all metrics, and a significant edge when event streams can be reused to perform more complex processing, indicating that less effort is necessary to extend functionality.

References

[1]
Agama web site. Web, 2011. http://www.agama.se.
[2]
B. Agarwal, S. Tayal, and M. Gupta. Software engineering & testing: an introduction. Jones & Bartlett Learning, 2010.
[3]
R. Al Qutaish and A. Abran. An Analysis of the Design and Definitions of Halstead's Metrics. In 15th Int. Workshop on Software Measurement (IWSM'2005). Shaker-Verlag, pages 337--352, 2005.
[4]
Altibox web site. Web, 2011. http://www.altibox.no.
[5]
M. Cha, P. Rodriguez, J. Crowcroft, S. Moon, and X. Amatriain. Watching Television over an IP Network. In IMC, 2008.
[6]
B. Curtis, S. B. Sheppard, P. Milliman, M. A. Borst, and T. Love. Measuring the Psychological Complexity of Software Maintenance Tasks with the Halstead and McCabe Metrics. IEEE Trans. Softw. Eng., 5:96--104, March 1979.
[7]
V. Da Yu Li and O. Ormandjieva. Halstead's Software Science in Today's Object Oriented World. Metrics News, pages 33--41, 2004.
[8]
J. Dean and S. Ghemawat. Mapreduce: simplified data processing on large clusters. Commun. ACM, 51:107--113, January 2008.
[9]
Esper documentation. Web, 2011. http://esper.codehaus.org/esper/documentation/documentation.html.
[10]
Esper, Performance-Related Information. Web, 2011. http://esper.codehaus.org/esper/performance/performance.html.
[11]
Hva er TNS Gallup TV-panel? (What is TNS Gallup TV-panel?). Web, 2011. http://www.tns-gallup.no/?aid=9072596.
[12]
P. G. Hamer and G. D. Frewin. M.H. Halstead's Software Science - a critical examination. In ICSE, 1982.
[13]
B. E. Helvik. Dependable Computing Systems and Communication Networks - Design and Evaluation. Tapir academic publisher, January 2009.
[14]
Latens web site. Web, 2011. http://www.latens.tv.
[15]
D. Logothetis, C. Olston, B. Reed, K. C. Webb, and K. Yocum. Stateful bulk processing for incremental analytics. In SoCC, 2010.
[16]
Mariner Partners - IPTV Monitoring Software. Web, 2011. http://www.marinerpartners.com.
[17]
A. Michlmayr, F. Rosenberg, P. Leitner, and S. Dustdar. Advanced event processing and notifications in service runtime environments. In DEBS, 2008.
[18]
Nielsen ratings. Web, 2011. http://en.wikipedia.org/wiki/Nielsen_ratings.
[19]
D. Nyvik. Cep: Integrator and facilitator for pub/sub messaging. December 2009.
[20]
J. Schmitt. NetComplete Home Performance Management (PM). White paper, November 2009. http://www.jdsu.com/ProductLiterature/netcompletehomepm_WP_sas_TM_AE.pdf.
[21]
V. Shen, S. Conte, and H. Dunsmore. Software Science Revisited: A Critical Analysis of the Theory and Its Empirical Support. IEEE Trans. Softw. Eng., 9:155--165, 1983.
[22]
K. Sripanidkulchai, B. Maggs, and H. Zhang. An analysis of live streaming workloads on the internet. In IMC, 2004.
[23]
Tns gallup. Web, 2011. http://www.tns-gallup.no.
[24]
H. Zuse. A Framework of Software Measurement. Walter de Gruyter & Co., Hawthorne, NJ, USA, 1997.

Cited By

View all
  • (2019)Shades of White: Impacts of Population Dynamics and TV Viewership on Available TV SpectrumIEEE Transactions on Vehicular Technology10.1109/TVT.2019.289286768:3(2427-2442)Online publication date: Mar-2019
  • (2018)A Fast Channel Change Technique Based on Channel PredictionIEEE Transactions on Consumer Electronics10.1109/TCE.2018.287527164:4(418-423)Online publication date: Nov-2018
  • (2014)P2SProceedings of the 8th ACM International Conference on Distributed Event-Based Systems10.1145/2611286.2611305(189-197)Online publication date: 26-May-2014
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
DEBS '11: Proceedings of the 5th ACM international conference on Distributed event-based system
July 2011
418 pages
ISBN:9781450304238
DOI:10.1145/2002259
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 July 2011

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. stream processing
  2. tv viewership statistics

Qualifiers

  • Research-article

Conference

DEBS '11

Acceptance Rates

DEBS '11 Paper Acceptance Rate 23 of 95 submissions, 24%;
Overall Acceptance Rate 145 of 583 submissions, 25%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)0
Reflects downloads up to 20 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2019)Shades of White: Impacts of Population Dynamics and TV Viewership on Available TV SpectrumIEEE Transactions on Vehicular Technology10.1109/TVT.2019.289286768:3(2427-2442)Online publication date: Mar-2019
  • (2018)A Fast Channel Change Technique Based on Channel PredictionIEEE Transactions on Consumer Electronics10.1109/TCE.2018.287527164:4(418-423)Online publication date: Nov-2018
  • (2014)P2SProceedings of the 8th ACM International Conference on Distributed Event-Based Systems10.1145/2611286.2611305(189-197)Online publication date: 26-May-2014
  • (2012)AdScorerProceedings of the 6th ACM International Conference on Distributed Event-Based Systems10.1145/2335484.2335494(85-94)Online publication date: 16-Jul-2012

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media