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Volume Leases for Consistency in LargeScale Jian Yin, Lorenzo Alvisi, Michael Dahlin, and Calvin Lin
 

Summary: 1
Volume Leases for Consistency in Large­Scale
Systems
Jian Yin, Lorenzo Alvisi, Michael Dahlin, and Calvin Lin
Computer Sciences Department
University of Texas at Austin
Abstract
This article introduces volume leases as a mechanism for providing server­driven cache consistency
for large­scale, geographically distributed networks. Volume leases retain the good performance, fault
tolerance, and server scalability of the semantically weaker client­driven protocols that are now used on
the web. Volume leases are a variation of object leases, which were originally designed for distributed file
systems. However, whereas traditional object leases amortize overheads over long lease periods, volume
leases exploit spatial locality to amortize overheads across multiple objects in a volume. This approach
allows systems to maintain good write performance even in the presence of failures. Using trace­driven
simulation, we compare three volume lease algorithms against four existing cache consistency algorithms
and show that our new algorithms provide strong consistency while maintaining scalability and fault­
tolerance. For a trace­based workload of web accesses, we find that volumes can reduce message traffic
at servers by 40% compared to a standard lease algorithm, and that volumes can considerably reduce
the peak load at servers when popular objects are modified.
Keywords

  

Source: Alvisi, Lorenzo - Department of Computer Sciences, University of Texas at Austin

 

Collections: Computer Technologies and Information Sciences