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The next-generation in-stadium experience (keynote)

The next-generation in-stadium experience (keynote)

Carnegie Mellon University, USA

Carnegie Mellon University, USA

Carnegie Mellon University, USA

Carnegie Mellon University, USA

Carnegie Mellon University, USA

Carnegie Mellon University, USA

Carnegie Mellon University, USA

Carnegie Mellon University, USA

Carnegie Mellon University, USA

Carnegie Mellon University, USA

    0 citation 270 Downloads

YinzCam is a cloud-hosted service that provides sports fans with real-time scores, news, photos, statistics, live radio, streaming video, etc., on their mobile devices. YinzCam’s infrastructure is currently hosted on Amazon Web Services (AWS) and supports over 30 million installs of the official mobile apps of 140+ NHL/NFL/NBA/NRL/NCAA sports teams and venues. YinzCam’s workload is necessarily multi-modal (e.g., pre-game, in-game, post-game, game-day, non-gameday), with normal game-time traffic being twenty-fold of that on non-game days. This paper describes the evolution of YinzCam’s production architecture and distributed infrastructure, from its beginnings in 2009, when it was used to support thousands of concurrent users, to today’s system that supports millions of concurrent users on any game day. We also discuss key new opportunities to improve the fan experience inside the stadium of the future, without impacting the available bandwidth, by crowd-sourcing the thousands of mobile devices that are in fans’ hands inside these venues. We present Krowd, a novel distributed key-value store for promoting efficient content sharing, discovery and retrieval across the mobile devices inside a stadium. We present CHIPS, a system that ensures that users’ privacy is maintained while their devices participate in the crowdsourced infrastructure.

  1. Computational Vision at CalTech. http://www.vision.caltech. edu/archive.html. Google Scholar
  2. OpenCV. http://opencv.org/. Google Scholar
  3. Cisco. Connecting Fans in New Ways to Deliver the Ultimate Fan Experience. Google Scholar
  4. ComputerWorld. Context on ice: Penguins fans get mobile extras. URL http://www.computerworld.com/s/article/9134588/ Context_on_ice_Penguins_fans_get_mobile_extras. Google Scholar
  5. M. Dano. Super Bowl traffic stats. http://goo.gl/uzMD2B. Google Scholar
  6. U. Drolia, N. Mickulicz, R. Gandhi, and P. Narasimhan. Krowd: A key-value store for crowded venues. In ACM International Workshop on Mobility in the Evolving Internet Architecture (MobiArch), 2015.

Google Scholar Digital Library

  • Extreme Marketing Team. In-Stadium Wi-Fi Analytics Reveal Fan Engagement At Super Bowl XLIX. http://goo.gl/piMmtQ. Google Scholar
  • S. Liao, X. Zhu, Z. Lei, L. Zhang, and S. Li. Learning Multi-scale Block Local Binary Patterns for Face Recognition. In International Conference on Biometrics (ICB), 2007.

    Google Scholar Digital Library
    N. Mickulicz, P. Narasimhan, and R. Gandhi. YinzCam: Experiences with In-Venue Mobile Video and Replays. In USENIX Large Installation System Administration Conference (LISA), 2013.

    Google Scholar Digital Library

  • N. Mickulicz, P. Narasimhan, and R. Gandhi. To Auto Scale or Not to Auto Scale. In International Conference on Autonomic Computing (ICAC), Management of Big Data Systems (MBDS) Track, 2013. Google Scholar
  • N. Mickulicz, R. Martins, P. Narasimhan, and R. Gandhi. When Good-Enough is Enough: Complex Queries at Fixed Cost. In IEEE International Conference on Big Data Computing Service and Applications (BigDataService), 2015. Google Scholar Digital Library
  • Mobile Marketer. 45.7% of sports fans use smartphones to access content online. URL http://www.mobilemarketer.com/cms/news/ research/14020.html. Google Scholar
  • M. Myreen and M. Gordon. Hoare Logic for Realistically Modeled Machine Code. In Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 2007.

    Google Scholar Digital Library
    M. Myreen, A. Fox, and M. Gordon. Hoare Logic for ARM Machine Code. In Fundamentals of Software Engineering (FSEN), 2007.

    Google Scholar Digital Library
    G. Necula and P. Lee. Safe kernel extensions without run-time checking. In USENIX Symposium on Operating System Design and Implementation (OSDI), Oct 1996.

    Читать еще:  Малокалиберный интернационал

    Google Scholar Digital Library

  • P. Narasimhan and R. Gandhi. Systems and methods for providing interactive video services. U.S. Patent US 9137495 B2. Google Scholar
  • K. Slind and M. Norrish. A Brief Overview of HOL4. In International Conference in Theorem Proving in Higher Order Logics (TPHOLs), 2008.

    Google Scholar Digital Library

  • P. Steinbach. Wi-Fi Service Increasingly Seen As a Must-Have Stadium Amenity. http://goo.gl/LCGCDv, July 2013. Google Scholar
  • J. Tan, U. Drolia, R. Martins, R. Gandhi, and P. Narasimhan. STOVEPipe: Observable Access Control of User Data for Untrusted Applications on Mobile Devices. In IEEE CloudCom (Poster Paper), 2014.

    Google Scholar Digital Library

  • < 20 >J. Tan, U. D rol i a, R Martins, R. Gandhi, and P. Narasimhan. Short P aper : C HI PS: Content — based H euristics for Improv i ng P hoto P rivacy for Smartphones. I n AC M Confere11ce 011 Security and Privacy i11 Wireless and Mobile Networks (WiSec), 20 1 4. < 21 >J. T an, R Gandhi, and P. Naras i mhan. STOVE : Strict, Observable, Verifiab l e D ata and E xecution Models for Untrusted Applications. I n IEEE CloudCom Doctoral Symposium, 20 1 4. < 22 >J. T an, H. T ay, R .Gandhi, and P. Naras i mhan. AUS P ICE : Automatic Safety P roperty Ver i fication for Unmodified Exec u tab l es. I n Working Confere11ce on Verified Software: Tools, Theories and Experimems (VSTTE ), 2015. Google Scholar
  • < 23 >M. T urk and A. P entland. E i genfaces for R ecogn i tion. Jour11al of Cognitive Neuroscience, 3(1), 1 991. < 24 >YinzCam, I nc. URL http : I/ vvw. yi nz c am. co m.

    YinzCam is a cloud-hosted service that provides sports fans with real-time scores, news, photos, statistics, live radio, streaming video, etc., on their mobile devices. YinzCam’s infrastructure is currently hosted on Amazon Web Services (AWS) and supports over 30 million installs of the official mobile apps of 140+ NHL/NFL/NBA/NRL/NCAA sports teams and venues. YinzCam’s workload is necessarily multi-modal (e.g., pre-game, in-game, post-game, game-day, non-gameday), with normal game-time traffic being twenty-fold of that on non-game days. This paper describes the evolution of YinzCam’s production architecture and distributed infrastructure, from its beginnings in 2009, when it was used to support thousands of concurrent users, to today’s system that supports millions of concurrent users on any game day. We also discuss key new opportunities to improve the fan experience inside the stadium of the future, without impacting the available bandwidth, by crowd-sourcing the thousands of mobile devices that are in fans’ hands inside these venues. We present Krowd, a novel distributed key-value store for promoting efficient content sharing, discovery and retrieval across the mobile devices inside a stadium. We present CHIPS, a system that ensures that users’ privacy is maintained while their devices participate in the crowdsourced infrastructure.

    1. Computational Vision at CalTech. http://www.vision.caltech. edu/archive.html. Google Scholar
    2. OpenCV. http://opencv.org/. Google Scholar
    3. Cisco. Connecting Fans in New Ways to Deliver the Ultimate Fan Experience. Google Scholar
    4. ComputerWorld. Context on ice: Penguins fans get mobile extras. URL http://www.computerworld.com/s/article/9134588/ Context_on_ice_Penguins_fans_get_mobile_extras. Google Scholar
    5. M. Dano. Super Bowl traffic stats. http://goo.gl/uzMD2B. Google Scholar
    6. U. Drolia, N. Mickulicz, R. Gandhi, and P. Narasimhan. Krowd: A key-value store for crowded venues. In ACM International Workshop on Mobility in the Evolving Internet Architecture (MobiArch), 2015.

    Google Scholar Digital Library

  • Extreme Marketing Team. In-Stadium Wi-Fi Analytics Reveal Fan Engagement At Super Bowl XLIX. http://goo.gl/piMmtQ. Google Scholar
  • S. Liao, X. Zhu, Z. Lei, L. Zhang, and S. Li. Learning Multi-scale Block Local Binary Patterns for Face Recognition. In International Conference on Biometrics (ICB), 2007.

    Google Scholar Digital Library
    N. Mickulicz, P. Narasimhan, and R. Gandhi. YinzCam: Experiences with In-Venue Mobile Video and Replays. In USENIX Large Installation System Administration Conference (LISA), 2013.

    Читать еще:  Фолклендская война: британский триумф в южной атлантике

    Google Scholar Digital Library

  • N. Mickulicz, P. Narasimhan, and R. Gandhi. To Auto Scale or Not to Auto Scale. In International Conference on Autonomic Computing (ICAC), Management of Big Data Systems (MBDS) Track, 2013. Google Scholar
  • N. Mickulicz, R. Martins, P. Narasimhan, and R. Gandhi. When Good-Enough is Enough: Complex Queries at Fixed Cost. In IEEE International Conference on Big Data Computing Service and Applications (BigDataService), 2015. Google Scholar Digital Library
  • Mobile Marketer. 45.7% of sports fans use smartphones to access content online. URL http://www.mobilemarketer.com/cms/news/ research/14020.html. Google Scholar
  • M. Myreen and M. Gordon. Hoare Logic for Realistically Modeled Machine Code. In Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 2007.

    Google Scholar Digital Library
    M. Myreen, A. Fox, and M. Gordon. Hoare Logic for ARM Machine Code. In Fundamentals of Software Engineering (FSEN), 2007.

    Google Scholar Digital Library
    G. Necula and P. Lee. Safe kernel extensions without run-time checking. In USENIX Symposium on Operating System Design and Implementation (OSDI), Oct 1996.

    Google Scholar Digital Library

  • P. Narasimhan and R. Gandhi. Systems and methods for providing interactive video services. U.S. Patent US 9137495 B2. Google Scholar
  • K. Slind and M. Norrish. A Brief Overview of HOL4. In International Conference in Theorem Proving in Higher Order Logics (TPHOLs), 2008.

    Google Scholar Digital Library

  • P. Steinbach. Wi-Fi Service Increasingly Seen As a Must-Have Stadium Amenity. http://goo.gl/LCGCDv, July 2013. Google Scholar
  • J. Tan, U. Drolia, R. Martins, R. Gandhi, and P. Narasimhan. STOVEPipe: Observable Access Control of User Data for Untrusted Applications on Mobile Devices. In IEEE CloudCom (Poster Paper), 2014.

    Google Scholar Digital Library

  • < 20 >J. Tan, U. D rol i a, R Martins, R. Gandhi, and P. Narasimhan. Short P aper : C HI PS: Content — based H euristics for Improv i ng P hoto P rivacy for Smartphones. I n AC M Confere11ce 011 Security and Privacy i11 Wireless and Mobile Networks (WiSec), 20 1 4. < 21 >J. T an, R Gandhi, and P. Naras i mhan. STOVE : Strict, Observable, Verifiab l e D ata and E xecution Models for Untrusted Applications. I n IEEE CloudCom Doctoral Symposium, 20 1 4. < 22 >J. T an, H. T ay, R .Gandhi, and P. Naras i mhan. AUS P ICE : Automatic Safety P roperty Ver i fication for Unmodified Exec u tab l es. I n Working Confere11ce on Verified Software: Tools, Theories and Experimems (VSTTE ), 2015. Google Scholar
  • < 23 >M. T urk and A. P entland. E i genfaces for R ecogn i tion. Jour11al of Cognitive Neuroscience, 3(1), 1 991. < 24 >YinzCam, I nc. URL http : I/ vvw. yi nz c am. co m.

    YinzCam is a cloud-hosted service that provides sports fans with real-time scores, news, photos, statistics, live radio, streaming video, etc., on their mobile devices. YinzCam’s infrastructure is currently hosted on Amazon Web Services (AWS) and supports over 30 million installs of the official mobile apps of 140+ NHL/NFL/NBA/NRL/NCAA sports teams and venues. YinzCam’s workload is necessarily multi-modal (e.g., pre-game, in-game, post-game, game-day, non-gameday), with normal game-time traffic being twenty-fold of that on non-game days. This paper describes the evolution of YinzCam’s production architecture and distributed infrastructure, from its beginnings in 2009, when it was used to support thousands of concurrent users, to today’s system that supports millions of concurrent users on any game day. We also discuss key new opportunities to improve the fan experience inside the stadium of the future, without impacting the available bandwidth, by crowd-sourcing the thousands of mobile devices that are in fans’ hands inside these venues. We present Krowd, a novel distributed key-value store for promoting efficient content sharing, discovery and retrieval across the mobile devices inside a stadium. We present CHIPS, a system that ensures that users’ privacy is maintained while their devices participate in the crowdsourced infrastructure.

    1. Computational Vision at CalTech. http://www.vision.caltech. edu/archive.html. Google Scholar
    2. OpenCV. http://opencv.org/. Google Scholar
    3. Cisco. Connecting Fans in New Ways to Deliver the Ultimate Fan Experience. Google Scholar
    4. ComputerWorld. Context on ice: Penguins fans get mobile extras. URL http://www.computerworld.com/s/article/9134588/ Context_on_ice_Penguins_fans_get_mobile_extras. Google Scholar
    5. M. Dano. Super Bowl traffic stats. http://goo.gl/uzMD2B. Google Scholar
    6. U. Drolia, N. Mickulicz, R. Gandhi, and P. Narasimhan. Krowd: A key-value store for crowded venues. In ACM International Workshop on Mobility in the Evolving Internet Architecture (MobiArch), 2015.
    Читать еще:  Германский линкор «тирпиц»: кошмар британского флота

    Google Scholar Digital Library

  • Extreme Marketing Team. In-Stadium Wi-Fi Analytics Reveal Fan Engagement At Super Bowl XLIX. http://goo.gl/piMmtQ. Google Scholar
  • S. Liao, X. Zhu, Z. Lei, L. Zhang, and S. Li. Learning Multi-scale Block Local Binary Patterns for Face Recognition. In International Conference on Biometrics (ICB), 2007.

    Google Scholar Digital Library
    N. Mickulicz, P. Narasimhan, and R. Gandhi. YinzCam: Experiences with In-Venue Mobile Video and Replays. In USENIX Large Installation System Administration Conference (LISA), 2013.

    Google Scholar Digital Library

  • N. Mickulicz, P. Narasimhan, and R. Gandhi. To Auto Scale or Not to Auto Scale. In International Conference on Autonomic Computing (ICAC), Management of Big Data Systems (MBDS) Track, 2013. Google Scholar
  • N. Mickulicz, R. Martins, P. Narasimhan, and R. Gandhi. When Good-Enough is Enough: Complex Queries at Fixed Cost. In IEEE International Conference on Big Data Computing Service and Applications (BigDataService), 2015. Google Scholar Digital Library
  • Mobile Marketer. 45.7% of sports fans use smartphones to access content online. URL http://www.mobilemarketer.com/cms/news/ research/14020.html. Google Scholar
  • M. Myreen and M. Gordon. Hoare Logic for Realistically Modeled Machine Code. In Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 2007.

    Google Scholar Digital Library
    M. Myreen, A. Fox, and M. Gordon. Hoare Logic for ARM Machine Code. In Fundamentals of Software Engineering (FSEN), 2007.

    Google Scholar Digital Library
    G. Necula and P. Lee. Safe kernel extensions without run-time checking. In USENIX Symposium on Operating System Design and Implementation (OSDI), Oct 1996.

    Google Scholar Digital Library

  • P. Narasimhan and R. Gandhi. Systems and methods for providing interactive video services. U.S. Patent US 9137495 B2. Google Scholar
  • K. Slind and M. Norrish. A Brief Overview of HOL4. In International Conference in Theorem Proving in Higher Order Logics (TPHOLs), 2008.

    Google Scholar Digital Library

  • P. Steinbach. Wi-Fi Service Increasingly Seen As a Must-Have Stadium Amenity. http://goo.gl/LCGCDv, July 2013. Google Scholar
  • J. Tan, U. Drolia, R. Martins, R. Gandhi, and P. Narasimhan. STOVEPipe: Observable Access Control of User Data for Untrusted Applications on Mobile Devices. In IEEE CloudCom (Poster Paper), 2014.

    Google Scholar Digital Library

  • < 20 >J. Tan, U. D rol i a, R Martins, R. Gandhi, and P. Narasimhan. Short P aper : C HI PS: Content — based H euristics for Improv i ng P hoto P rivacy for Smartphones. I n AC M Confere11ce 011 Security and Privacy i11 Wireless and Mobile Networks (WiSec), 20 1 4. < 21 >J. T an, R Gandhi, and P. Naras i mhan. STOVE : Strict, Observable, Verifiab l e D ata and E xecution Models for Untrusted Applications. I n IEEE CloudCom Doctoral Symposium, 20 1 4. < 22 >J. T an, H. T ay, R .Gandhi, and P. Naras i mhan. AUS P ICE : Automatic Safety P roperty Ver i fication for Unmodified Exec u tab l es. I n Working Confere11ce on Verified Software: Tools, Theories and Experimems (VSTTE ), 2015. Google Scholar
  • < 23 >M. T urk and A. P entland. E i genfaces for R ecogn i tion. Jour11al of Cognitive Neuroscience, 3(1), 1 991. < 24 >YinzCam, I nc. URL http : I/ vvw. yi nz c am. co m.

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