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UID:www.tcs.tifr.res.in/event/249
DTSTAMP:20230914T125916Z
SUMMARY:Fault Tolerance in Distributed Systems: A Coding-Theoretic Approach
DESCRIPTION:Speaker: Bharath B.\nThe University of Texas at Austin\nElectri
 cal and Computer Engineering\n1 University Station C0803\nAustin\, TX 7871
 2\nUnited States of America\n\nAbstract: \nDistributed systems are rapidly
  increasing in importance due to the need for scalable computation on huge
  volumes of data. This fact is reflected in many distributed applications 
 such as Amazon’s cloud computing service\, Google’s BigTable or Apache
 ’s Hadoop framework. Replication is the prevalent solution for fault tol
 erance in these systems. This solution\, though simple\, is wasteful in te
 rms of both the space and infrastructure costs required to host the backup
 s. We present a new paradigm to solve this problem\, broadly referred to a
 s fusion\, that combines the operational efficiency of replication with th
 e space efficiency of coding theory. To make our techniques generally appl
 icable\, we describe fusion in two separate contexts: finite state machine
 s and infinite state machines.\n\nFor finite state machines\, we present a
  polynomial time algorithm to generate efficient backup machines. For infi
 nite state machines\, we consider programs that host large data structures
  such as linked lists\, stacks\, vectors and maps. Using a combination of 
 erasure codes and selective replication\, we present an algorithm to gener
 ate efficient backup data structures. We prove the minimality of our schem
 es and also provide experimental results that confirm the same. Finally\, 
 we present a fusion-based design for fault tolerance in two real world app
 lications: Amazon’s key-value store\, Dynamo\, and Google's Map Reduce f
 ramework\, that is much more efficient than the current replication-based 
 approach.\n
URL:https://www.tcs.tifr.res.in/web/events/249
DTSTART;TZID=Asia/Kolkata:20120206T160000
DTEND;TZID=Asia/Kolkata:20120206T170000
LOCATION:AG-66 (Lecture Theatre)
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