Download Virtual Full Replication for Scalable Distributed Real-Time Databases Gunnar Mathiason

Linköping Studies in Science and Technology
Dissertation No. 1281
Virtual Full Replication for
Scalable Distributed Real-Time Databases
by
Gunnar Mathiason
Akademisk avhandling
som för avläggande av teknologie doktorsexamen vid Linköpings universitet kommer att
offentligt försvaras i Insikten, Portalen, Högskolan i Skövde, fredagen den 18 december 2009,
kl 13.15.
Abstract
A fully replicated distributed real-time database provides high availability and predictable
access times, independent of user location, since all the data is available at each node.
However, full replication requires that all updates are replicated to every node, resulting in
exponential growth of bandwidth and processing demands with the number of nodes and
objects added. To eliminate this scalability problem, while retaining the advantages of full
replication, this thesis explores Virtual Full Replication (ViFuR); a technique that gives
database users a perception of using a fully replicated database while only replicating a subset
of the data.
We use ViFuR in a distributed main memory real-time database where timely transaction
execution is required. ViFuR enables scalability by replicating only data used at the local
nodes. Also, ViFuR enables flexibility by adaptively replicating the currently used data,
effectively providing logical availability of all data objects. Hence, ViFuR substantially
reduces the problem of non-scalable resource usage of full replication, while allowing timely
execution and access to arbitrary data objects.
In the thesis we pursue ViFuR by exploring the use of database segmentation. We give a
scheme (ViFuR-S) for static segmentation of the database prior to execution, where access
patterns are known a priori. We also give an adaptive scheme (ViFuR-A) that changes
segmentation during execution to meet the evolving needs of database users. Further, we
apply an extended approach of adaptive segmentation (ViFuR-ASN) in a wireless sensor
network - a typical dynamic large-scale and resource-constrained environment. We use up to
several hundreds of nodes and thousands of objects per node, and apply a typical periodic
transaction workload with operation modes where the used data set changes dynamically. We
show that when replacing full replication with ViFuR, resource usage scales linearly with the
required number of concurrent replicas, rather than exponentially with the system size.
This work has been supported by CUGS and University of Skövde.
Department of Computer and Information Science
Linköpings universitet
SE-581 83 Linköping, Sweden
ISBN 978-91-7393-503-6
ISSN 0345-7524