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SUMMARY:On User Availability Prediction And Network Applications - Matteo 
 Dell'Amico (Eurecom)
DTSTART:20111213T110000Z
DTEND:20111213T120000Z
UID:TALK34884@talks.cam.ac.uk
CONTACT:Eiko Yoneki
DESCRIPTION:User connectivity patterns in network applications are known t
 o be heterogeneous\, and to follow periodic (daily and weekly) patterns.\n
 In many cases\, the regularity and the correlation of those patterns is pr
 oblematic: for network applications\, many connected users create peaks of
  demand\; in peer-to-peer scenarios\, having few users online additionally
  results in a scarcity of available resources.\n\nOn the other hand\, sinc
 e connectivity patterns exhibit a periodic behavior\, they are to some ext
 ent predictable. This work shows how this can be exploited to anticipate f
 uture user connectivity and to have applications proactively responding to
  it. We evaluate the probability that any given user will be online at any
  given time\, and assess the prediction on six-month availability traces f
 rom three different Internet applications.\n\nBuilding upon this\, we show
  how our probabilistic approach makes it easy to evaluate and optimize the
  performance in a number of diverse network application models\, and to us
 e them to optimize systems. In particular\, we show how this approach can 
 be used in distributed hash tables\, friend-to-friend storage\, and cache 
 pre-loading for social networks\, resulting in substantial gains in data a
 vailability and system efficiency at negligible costs.\n
LOCATION:FW11\, Computer Laboratory\, William Gates Builiding
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