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UID:www.tcs.tifr.res.in/event/773
DTSTAMP:20230914T125937Z
SUMMARY:Content Caching and Delivery with Partial Adaptive Matching
DESCRIPTION:Speaker: Nikhil Karamchandani (Indian Institute of Technology\n
 Department of Electrical Engineering\nPowai\nMumbai 400076)\n\nAbstract: \
 nCaching of popular content during off-peak hours is a strategy to reduce
  the network load during peak hours. We consider a model where multiple c
 aches store pre-fetched content and when users request files\, they are ma
 tched to caches based on the request pattern. In particular\, we focus on 
 the case where caches are divided into clusters and each user can only be 
 assigned to a unique cache from a specific cluster. This is a generalizati
 on of two popular models which are the extremes of the proposed model: one
  where each user is pre-attached to a cache irrespective of what it demand
 s (static matching) and the other where each user can be assigned to any c
 ache in the entire network (fully adaptive matching).  We show that neith
 er the coded delivery strategy (approximately optimal when the user-cache 
 assignment is pre-fixed) nor the uncoded replication strategy (approximate
 ly optimal when all caches belong to a single cluster) is sufficient for a
 ll memory regimes. We propose a hybrid solution that combines ideas from b
 oth schemes and that performs strictly better than both. Finally\, we show
  that this hybrid strategy is approximately optimal in most memory regimes
 .\n
URL:https://www.tcs.tifr.res.in/web/events/773
DTSTART;TZID=Asia/Kolkata:20170425T160000
DTEND;TZID=Asia/Kolkata:20170425T170000
LOCATION:A-201 (STCS Seminar Room)
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