NII Shonan Meeting: Work

Suresh has blogged extensively about the workshop on large scale distributed computing, so I have only \eps to add. Btw, talk abstracts and slides can be found here.

At high level, there were three models discussed: streaming (S); mapreduce/DHTs based computing (M); distributed, continuous monitoring (DCM). New variations of these models continue to be identified, and while probably algorithmic techniques for S are probably the most developed, increasingly more results are appearing in M and DCM. Eventually, it will be nice to see some general reductions and relationships between these models. There were several database researchers at the meeting.

About specific problems: Qin Zhang talked about tight bounds for various frequency moments in DCM closing out several open problems; Amr Abbadi rose to the occasion to engage the theoretician by posing a simple social network based variants of heavy hitters that is challenging; Suresh spoke about a nice formulation of distributed learning. Minos Garofalakis talked about some nifty prediction schemes so that individual, distributed sensors need to hardly send any bits to the center, and yet the center can track sophisticated functions on the sensor readings. I liked Amr's comment how DCM is related to view maintenance in databases.