SAR: semantic-aware replication
Abstract
This dissertation presents a replication framework that facilitates semantic-aware data
replication (SAR) in wide area networks (WANs). WAN data replication is fundamentally
difficult. As a result, generic replication algorithms must make compromises among
Consistency, Availability, Response time, and Partition resilience (CARP) when used in
WANs. This dissertation seeks to design algorithms based on specific semantics of the
shared data sets (e.g. data properties, workload characteristics, and update patterns) to
achieve the optimized CARP trade-offs. Integrating a set of semantic-aware algorithms using
distributed objects to form the SAR framework, we implement a practically important
e-commerce application, the distributed TPC-W benchmark. Our prototype evaluations
show significant improvements on system availability and response time while preserving
the consistency guarantees desired by the TPC-W benchmark. The primary focus of the
dissertation is on the development of the SAR framework. Within the framework, contributions
include (a) exploiting application semantics using the object-oriented approach,
(b) employing a hybrid method that integrates a number of novel replication algorithms to
make an important class of applications work, (c) proposing a novel replication algorithm
for the multi-writer/multi-reader replication scenario with a high access locality, and (d)
outlining a general purpose replication library that uses semantic-aware objects for building
other distributed applications in WANs.
Department
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