The long interesting tail of indie tv
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The long, interesting tail of Indie TV. Daniel Cutting, Aaron Quigley, Björn Landfeldt CTSB Workshop, Pervasive 2006, 7th May 2006. Indie TV. Producing video content is now easy and cheap More publishers and more niche content

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The long interesting tail of indie tv

The long, interesting tail of Indie TV

Daniel Cutting, Aaron Quigley, Björn Landfeldt

CTSB Workshop, Pervasive 2006, 7th May 2006


Indie tv

Indie TV

  • Producing video content is now easy and cheap

    • More publishers and more niche content

  • Already specialised TV channels on the web appealing to niche audiences

    • Sail.tv, Democracy TV, YUKS TV

  • Logical conclusion is a tailored channel for each viewer based specifically on their interests


Indie tv1

Indie TV

  • Indie TV has 3 components, Creators, the Disseminator, and Blenders

  • Content is produced by creators who describe its audience in terms of interests

    • E.g. a dramatic thriller is destined for an audience interested in “drama” and “thrillers”

  • The Disseminator delivers the content to this audience

  • The Blenders combine content as it arrives for playback

  • We focused on the dissemination aspect only


Indie tv2

Indie TV


Dissemination via implicit groups

Dissemination via “implicit groups”.

  • Explicit groups

    • Viewers named

    • Pre-defined by creator or viewers need to join

    • Kim, Julie

  • Implicit groups

    • Viewers described

    • Creator defines “on the fly”, viewers don’t need to join

    • Drama & Thriller


Implicit group messaging

Implicit group messaging.

  • Multicast messages from any source to any implicit group at any time in a P2P network

    • Each peer described by interests, e.g. “Drama”, “Sci-Fi”

    • Implicit groups are specified as logical expressions of attributes, e.g. “Drama AND Thriller”

    • System delivers messages from creators to all viewers matching target expressions

  • Iterative design process

    • Theoretical, implementation, simulation, theoretical…


Initial theoretical model

Initial theoretical model.

  • A fully distributed, structured overlay network

    • Peers maintain a logical Cartesian surface (like CAN)

    • Each peer owns part of the surface and knows neighbours

    • Peers geometrically ROUTE to locations by passing from neighbour to neighbour


Initial theoretical model1

Initial theoretical model.

  • Peers’ locations on the surface determined by their attributes

Benoit {Action, Thriller}

Kim {Drama, Sci-Fi, Thriller}

Julie {Drama, Thriller, Romance, Action}


Initial theoretical model2

Initial theoretical model.

  • Can calculate all regions on the surface where the matching viewers must exist

  • Multicast content from creators to the regions matching the audience description


Initial implementation

Initial implementation.

  • OMNeT++/INET simulation of a real network

  • The simulation raised some concerns we had not considered in the initial design

    • The overlay hop between peers on the surface resulted in many IP hops at the network layer which led to extremely long end-to-end delays

    • The design was adequate for large/medium implicit groups but required too much overhead for small groups


Revised theoretical model

Revised theoretical model.

  • The simulation led us to revise the model taking these problems into account

  • To counter the latency problem, we stored pointers to the peers on the surface, rather than locate the peers there themselves

    • This allowed us to have peers that were physically close to be close on the surface, regardless of their attributes

  • To counter the group size problem, we introduced a hybrid approach

    • Smaller groups used a distributed index to find members

    • Initial model retained for large groups


Distributed index

Distributed index.

  • Every peer registers at a rendezvous point (RP) for each of its attributes

  • Every registration includes IP address and all attributes


Distributed index1

Distributed index.

  • To CAST, select one term from target

  • Route CAST to its RP

  • RP finds all matches and unicasts to each


Evaluation

Evaluation.

  • New implementation’s performance was vastly better

    • Delay was greatly reduced and within required limits

    • Overall network peer and link stress was also reduced, especially when delivering content to small or empty groups (load was now proportional to group size)


Conclusion

Conclusion.

  • We had an elegant theoretical model to begin with

  • But, abstracted details of the system too much

    • A structured overlay network has to be based upon physical computer network with peers, routers, fast and slow network links

    • The possibility of highly variable group sizes had been similarly neglected

  • Implementing the simulation brought these problems to the fore and allowed a quick revision of the theoretical model


Questions

Questions?


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