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Volume Leases for Consistency in Large-Scale Systems
July/August 1999 (vol. 11 no. 4)
pp. 563-576
ASCII Text
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Jian Yin, Lorenzo Alvisi, Michael Dahlin, Calvin Lin, "Volume Leases for Consistency in Large-Scale Systems," IEEE Transactions on Knowledge and Data Engineering, vol. 11, no. 4, pp. 563-576, July/August, 1999.
 
 
BibTex
x
 
@article{ 10.1109/69.790806,
author = {Jian Yin and Lorenzo Alvisi and Michael Dahlin and Calvin Lin},
title = {Volume Leases for Consistency in Large-Scale Systems},
journal ={IEEE Transactions on Knowledge and Data Engineering},
volume = {11},
number = {4},
issn = {1041-4347},
year = {1999},
pages = {563-576},
doi = {http://doi.ieeecomputersociety.org/10.1109/69.790806},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Knowledge and Data Engineering
TI - Volume Leases for Consistency in Large-Scale Systems
IS - 4
SN - 1041-4347
SP563
EP576
EPD - 563-576
A1 - Jian Yin,
A1 - Lorenzo Alvisi,
A1 - Michael Dahlin,
A1 - Calvin Lin,
PY - 1999
KW - Cache consistency
KW - lease
KW - volume
KW - fault tolerance
KW - scalable server
KW - file system.
VL - 11
JA - IEEE Transactions on Knowledge and Data Engineering
ER -
 

Abstract—This article introduces volume leases as a mechanism for providing server-driven cache consistency for large-scale, geographically distributed networks. Volume leases retain the good performance, fault tolerance, and server scalability of the semantically weaker client-driven 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 trace-driven 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 trace-based workload of web accesses, we find that volumes can reduce message traffic at servers by 40 percent compared to a standard lease algorithm, and that volumes can considerably reduce the peak load at servers when popular objects are modified.

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Index Terms:
Cache consistency, lease, volume, fault tolerance, scalable server, file system.
Citation:
Jian Yin, Lorenzo Alvisi, Michael Dahlin, Calvin Lin, "Volume Leases for Consistency in Large-Scale Systems," IEEE Transactions on Knowledge and Data Engineering, vol. 11, no. 4, pp. 563-576, July-Aug. 1999, doi:10.1109/69.790806
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