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INTRODUCTION
experts, which usually customize WSNs manually
to application and deployment requirements. It is
an obvious fact that most approaches for WSNs
hardly consider or even disregard the configuration
complexity of a WSN. However, a proper usability
is considered essential for WSNs supporting real
life applications. Making the programming and
deployment of a WSN accessible for non-experts
could become the most important issue in order
to gain broad consumer acceptance of WSNs.
Pervasive systems are expected to consist
of various devices providing different capabili-
ties, hardware and software. Approaches aiming
at ease of use for specifying new applications
have to autonomously cope with expected and
unexpected heterogeneity, fault tolerance and
energy efficiency. Provision of means that enable
non-professional users to make use of the WSN
is required to make them widely accepted. These
users are usually short on experience of program-
ming languages and sensor networks. They cannot
be asked for applying programming languages or
data-base abstractions for WSN configuration.
These users require a straightforward method
for task definition and sensor node configura-
tion without the need to know about hard- or
software or node deployment of the WSN under
configuration. Further, the algorithms used for
configuration of the sensor nodes must be robust
enough to autonomously overcome sudden failures
during runtime, such as unavailability of sensing
features or of collaborating nodes. Nevertheless,
all necessary internal configuration and adapta-
tion processes have to be completely hidden from
the user.
This chapter introduces general design criteria
for application design in WSNs. Based on these
design criteria, this chapter motivates a signifi-
cant change from a WSN-centric to user-centric
design flow of pervasive applications. Instead of
customizing applications to the conditions of the
deployed WSN, which is the WSN-centric design,
Pervasive computing significantly increases
the human-computer interaction as well as the
environment-computer interaction and enables
a direct interplay between the real world and the
information technology. The vision of pervasive
intelligent environments surrounding and serving
us at any place and any time will become reality
in the near future. Computing devices will be
embedded in everyday objects allowing informa-
tion technology to fade into the background and
become nearly invisible to their users. Wireless
Sensor Networks (WSNs) are one of the first real
world examples enabling pervasive computing.
Envisioned to be distributed like “Smart Dust”,
these networks support a broad range of applica-
tions and may become the perfect service and
surveillance tool. Based on their capability to
identify physical phenomena, sensor networks
can be applied for environmental and structural
control, context-awareness for personal services,
military applications or pervasive healthcare, to
mention a few (Mainwaring, Culler, Polastre,
Szewczyk, & Anderson, 2002; Werner-Allen,
Johnson, Ruiz, Lees, & Welsh, 2005; Akyildiz, Su,
Sankarasubramaniam, & Cayirci, 2002; Aboelaze
& Aloul, 2005). To summarize, ambient assist-
ing technology based on WSNs will amazingly
increase our quality of life.
Despite of the emerging advantages and poten-
tial applications, there are still a lot of challenges
and problems to solve before WSNs can be used
as consumer technology. WSNs are expected to be
deployed with high density in large areas where
hundreds or thousands of nodes are used. Due to
the pervasiveness of envisioned systems, those are
caught in a crossfire of external and internal influ-
ences. Sudden changes in operational conditions,
varying deployment and hazardous environments
adversely affect the reliability of applications. The
configuration of a pervasive system is yet hard for
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