10.2417/2200809.1262
An open-source infrastructure
for pervasive computing
Simon Dobson, Graeme Stevenson, Graham Williamson,
Stephen Knox, Matthew Stabeler, Lorcan Coyle, Steve Neely,
and Paddy Nixon
New software for gathering and disseminating information makes it
easier to develop services for sensor-rich environments.
Pervasive computing provides a means of broadening and deep-
ening the reach of information technology (IT) in society. It can
be used to simplify interactions with Web sites, provide ad-
vanced location-specific services for people on the move, and
support all aspects of citizens’ life in the community. Integrat-
ing IT services into everyday life requires that we can sense the
environment where services are offered, and tailor them as the
environment changes. People are not automata, however, and
will often perform the same activity in slightly different ways.
Moreover, the methods used to sense a person’s actions are in-
herently error-prone and imprecise, and the same events may be
observed from different sensors or information sources. Users’
support needs also evolve over time. These triple problems of sit-
uation identification, context fusion, and behavioural evolution con-
stitute the major challenges to building robust pervasive appli-
cations or services.
Implementing individual pervasive applications, such as tour
guides1 or healthcare,2 has been straightforward. But it has
proved more difficult to build pervasive systems in which a dy-
namic population of services share infrastructure, sensing, and
capabilities. Each new system requires a considerable invest-
ment of time to acquire expertise and money to create the neces-
sary infrastructure. We aim to reduce these barriers and simplify
the construction of extensible, long-lived pervasive systems.
We have developed our system, Construct, by identifying
the best-of-breed techniques that have been successfully imple-
mented for pervasive systems. We have collected these together
into a middleware platform, an intermediary between sensors
and services. Construct provides a uniform framework for sit-
uation identification and context fusion, while providing trans-
parent data dissemination and node management.3
Construct’s basic architecture (see Figure 1) relies on services
and sensors that access a distributed collection of nodes, which
are responsible for aggregating data from the sensors. Construct
Figure 1. Data from sensors like Bluetooth or RFID is aggregated by
nodes, which then disseminate the information.
regards all data sources as sensors: for example, physical ones
for temperature, pressure, and location are included along with
virtual ones that access digital and Web resources.
A sensor injects information into Construct’s resource de-
scription framework (RDF) triple-store4 database. The triple
store provides a set of common descriptions for concepts
across domains.5 This model means that different sensors
can be used to detect the same information. Location may
be sensed directly from RFID (radio frequency identifica-
tion) or Ubisense, or inferred from diary or proximity in-
formation. Yet all this information can be accessed by
services using a common data model. To request information
from the database, applications query the triple store using the
standard SPARQL language.
Construct does not provide remote access to sensors: instead,
sensor data is transmitted around the network using the Zero-
conf protocol6 for node discovery and gossiping to exchange
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10.2417/2200809.1262 Page 2/2
data.7 Gossiping means that nodes randomly synchronise their
triple stores. This can lead to substantial background communi-
cations traffic, but increases the robustness of the system, since a
node failure will not cause sensed data to be lost. It can also im-
prove responsiveness, since all requests for information from the
database are performed locally. Taken together, these approaches
mean that developers need never deal with distributed systems
issues, since these are taken care of by the middleware. The Con-
struct architecture is completely modular, allowing us to experi-
ment with data dissemination protocols like adaptive gossiping8
and piggybacking.
We used a suite of sensors including Ubisense, Bluetooth lo-
cation, diary and web scraping for an example service called
Basadaeir (the Irish word for matchmaker). This program aims
to provide a context-sensitive display of information that inter-
ests a group of people. We use Bluetooth sensing of people’s mo-
bile phones to detect their presence near the display, and fuse
this with information about their research interests, available pa-
pers and events, and joint projects. The resulting display shows
information tied to the common research interests of the individ-
uals present, by using a combination of location sensing, digital
information and social networking.
Construct provides a useful platform for both researchers and
practitioners. By providing a foundation for creating and ex-
changing components, we aim to simplify the development of
systems, and speed up the convergence of best practices and
design patterns. Our next steps include increasing the popu-
lation of sensors and exploring alternative gossiping strategies
that can reduce communications overhead. Beta-test releases of
Construct and various sensors are available.9
This work is partially supported by Science Foundation Ireland under
grants 04/RPI/1544, ‘Secure and Predictable Pervasive Computing,’
03/CE2/I303-1, ‘Lero: The Irish Software engineering Research Cen-
tre,’ and 05/RFP/CMS0062, ‘Towards a Semantics of Pervasive Com-
puting.’
Author Information
Simon Dobson, Graeme Stevenson, Graham Williamson,
Stephen Knox, Matthew Stabeler, Lorcan Coyle, Steve Neely,
and Paddy Nixon
School of Computer Science and Informatics
University College Dublin
Dublin, Ireland
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