Pervasive and Mobile Computing 6 (2010) 218–238
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Pervasive and Mobile Computing
journal homepage: www.elsevier.com/locate/pmc
Optimising context data dissemination and storage in distributed
pervasive computing systems
Ioanna Roussaki
a,∗
, Maria Strimpakou
a
, Carsten Pils
b
, Nikos Kalatzis
a
, Nicolas Liampotis
a
a
National Technical University of Athens, School of Electrical and Computer Engineering, 9 Heroon Polytechneiou Street, 15773 Zographou, Athens, Greece
b
Waterford Institute of Technology, Telecommunications Software & Systems Group, Waterford, Ireland
article info
Article history:
Received 28 February 2008
Received in revised form 26 April 2009
Accepted 1 July 2009
Available online 19 July 2009
Keywords:
Context Distributed Database Management
System
Context management & query languages
Mobile physical object handling
Context replication
Selective context data dissemination
abstract
Context management systems are expected to administrate large volumes of spatial
and non-spatial information in geographical disperse domains. In particular, when these
systems cover wide areas such as cities, countries or even the entire planet, the
design of scalable storage, retrieval and propagation mechanisms is paramount. This
paper elaborates on mechanisms that address advanced requirements, including support
for distributed context databases management; efficient query handling; innovative
management of mobile physical objects and optimization strategies for distributed
context data dissemination. These mechanisms establish a robust spatially-enhanced
distributed context management framework that has already been designed and carefully
implemented and thoroughly evaluated.
© 2009 Elsevier B.V. All rights reserved.
1. Introduction
Network operators, sensor networks or even web resources capture valuable information such as device location and
status, user profiles and movement patterns, network performance, etc., in order to provide enhanced telecommunication
services to their clients. This data is considered to be vital context information [1] that can be exploited to customize
services, to anticipate user intentions and to ultimately reduce human-to-machine interactions [2]. However, even though
context information holds out the prospect of enhancing user experience and increasing revenues, disseminating it across
distributed nodes is not straightforward. On the one hand, the various infrastructures that store and manage context data
are heterogeneous, while there is no standardized interface that supports context information exchange. On the other hand,
information, which cannot be retrieved when necessary, is valueless. In an open context marketplace, where a wide variety
of information types is traded, context consumers are challenged by the discovery of the required context data. In this
perspective, timely delivery of context information is crucial, due to the fact that most data sources provide real-time
information. Thus, efficient approaches for distributed storage, retrieval and timely delivery of context data are essential
for the success of context-aware computing systems. In particular, when context aware systems are not confined to a single
building, but extend their functionality to cities, countries or even the entire planet, scalable and efficient data distribution
mechanisms are paramount.
In order to support the provision of personalized and context aware services, irrespective of the user device and the
underlying network, information originating from multiple context providers is usually required [3]. These context providers
do not necessarily belong to the same legal entity or administrative domain. In such a federated context management
∗
Corresponding author. Tel.: +30 210 772 24 22; fax: +30 210 772 25 30.
E-mail addresses: nanario@telecom.ntua.gr (I. Roussaki), mstrim@telecom.ntua.gr (M. Strimpakou), cpils@tssg.org (C. Pils), nikosk@telecom.ntua.gr
(N. Kalatzis), nliam@telecom.ntua.gr (N. Liampotis).
1574-1192/$ – see front matter © 2009 Elsevier B.V. All rights reserved.
doi:10.1016/j.pmcj.2009.07.015