In this project, we are investigating the theory, algorithms and applications of fusible data structures for fault-tolerance in parallel or distributed programs with low overhead. Fusible data structures are based on combining partial replication with erasure coding to satisfy three main properties: recovery, space constraint and efficient maintenance. The recovery property ensures that in case of a failure, the fused structure, along with the remaining original data structures, can be used to reconstruct the failed structure. The space constraint ensures that the number of nodes in the fused structures is strictly smaller than the number of nodes in the original structures. Finally, the efficient maintenance property ensures that when any of the original data structures is updated, the fused structure can be updated incrementally using local information about the update and does not need to be entirely recomputed.

The project is carrying out the following three tasks: (i) develop algorithms for fusible data structures for other commonly used structures such as trees and graphs, (ii) develop theory and associated algorithms for multiple faults (iii) apply fusible data structures for recovery of parallel and distributed applications and evaluate the performance benefits of our approach in real applications.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Application #
0718990
Program Officer
D. Helen Gill
Project Start
Project End
Budget Start
2007-09-01
Budget End
2011-08-31
Support Year
Fiscal Year
2007
Total Cost
$242,332
Indirect Cost
Name
University of Texas Austin
Department
Type
DUNS #
City
Austin
State
TX
Country
United States
Zip Code
78712