MediaNet

MediaNet is a distribution network for streaming data.  While the model is fairly general, our inspiration and current target has been to determine how to best deliver reconnaissance data (video and other relevant conditions) from a fleet of UAV's (Unmanned Aerial Vehicles) to a network of command and control centers.  The technical challenge is to deliver the data in resource-limited, small-scale (in terms of number of nodes, not necessarily distance between them) environments meeting the preferences and demands of the target control applications.

The MediaNet architecture is roughly as follows

• It uses a computational, overlay network to manage data delivery and user preferences.  User preferences are specified as graphs of computations, called continuous media networks, encoded in XML.  Each node in the graph transforms the incoming stream, and sends output to zero or more downstream nodes.
• To ensure good quality of service, a system-wide scheduler performs adaptive allocation of the nodes in the user preferences graph to nodes in the network; more than one user computation may be scheduled on a single network node.  In resource-limited situations, this allocation takes into account user preferences for adaptation.  In particular, the user will specify a series of graphs, all with a corresponding "utility" indicating the user's preference.

While MediaNet currently targets multimedia streams, our model is general enough to apply to more arbitrary distributed computations.  MediaNet compute nodes are written in Cyclone, a type-safe systems programming language.

We are currently working on a measurement-enabled transport layer to more efficiently discover available resources for making smarter scheduling decisions.

People

• Michael Hicks
• Pavlos Papageorgiou
  
• Robbert Van Renesse (former member, @Cornell University)

Papers and Software

Merging Network Measurement with Data Transport (Extended Abstract).  Pavlos Papageorgiou and Michael Hicks.  In Proceedings of the IEEE Passive/Active Measurement Workshop  (PAM), March 2005.  PDF. Poster PDF

User-specified Adaptive Scheduling in a Streaming Media Network.  Michael Hicks, Adithya Nagarajan, and Robbert van Renesse.  IEEE OPENARCH 2003. PS PDF PowerPoint

User-specified Adaptive Scheduling in a Streaming Media Network.  Michael Hicks, Robbert van Renesse, Mark Bickford, Robert Constable, Christoph Kreitz, and Lori Lorigo.  Cornell Technical Report, June 2002. (A forthcoming Technical Report will supercede this one; stay tuned!) PS PDF

Download MediaNet 0.1beta. To build this, you'll need Cyclone version 0.8 (and gcc).

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