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Fri, 15 Nov 2019 02:41:24 +0100
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Federico Montori <[log in to unmask]>
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Information Quality and Quality of Service for Pervasive Computing
(IQ2S2020)
Austin, Texas USA March 23-27 2020 (co-located with IEEE PerCom 2020)

Pervasive computing provides an exciting paradigm for supporting
anywhere anytime services, and is built on the tremendous advances made
in a broad spectrum of technologies including wireless communication,
wireless and sensor networking, mobile and distributed computing, as
well as signal and information processing. Pervasive computing enables
computers to interact with the real world in a ubiquitous and natural
manner. Quality of service (QoS), related to transmission delay,
bandwidth, or packet loss, has been studied in various building blocks
in pervasive computing, e.g., different QoS mechanisms are presented for
wireless or wired networks; the notion of computational QoS is used for
parallel processing. The emerging pervasive computing paradigm, however,
is application-driven and mission-critical and the existing QoS notions
to do not really match. Quality of Information (QoI) or Information
Quality (IQ) of sensor-originated information relates to the fitness of
the information for a sensor-enabled application. Harnessing and
optimizing QoI of information derived from sensor networks will be key
to bringing together information acquisition and processing systems that
support the on-demand information needs of a broad spectrum of smart,
sensor-enabled applications such as remote real-time habitat monitoring,
utility grid monitoring, environmental control, supply-chain management,
health care, machinery control, intelligent highways, military
intelligence, reconnaissance and surveillance (ISR), border control, and
hazardous material monitoring, just to mention a few.

The proliferation of smartphone has also enabled the possibility to
retrieve data also by users on the move. This data collection paradigm
is often called crowdsensing, or crowdsourcing, and builds upon the
willingness of users to share data together, which eventually gets
aggregated to provide novel services to the community.

Although fascinating, and potentially disruptive, this paradigm
inherently carries a set of technical challenges, at various levels and
which should be studied by different research communities. At first, to
make the data granularity spread enough, the crowd should be
sufficiently large. This means that the application which runs on the
users’ device has to be optimized, and should not interfere with the
normal activity the users want to perform. This raises the challenge of
having smart interfaces which communicate with the user only when
necessary, along with the battery efficiency, which plays a crucial role
being these devices almost always battery powered. Another technical
challenge comes from the heterogeneous data aggregation, as data can be
in many different shapes, formats, and labeled in different languages.
Hence, automatically linking data that comes from different platforms
becomes challenging, and again clustering techniques, supervised and
unsupervised machine learning algorithms have to be developed to perform
such task efficiently.

Achieving the desired “pervasiveness” of mobile applications, which in
turns enable to retrieve data for the community, and the assessment of
the QoI itself is key.

The objective of this workshop (which is unique venue in its scope for
the pervasive community) is to provide a forum to exchange ideas,
present results, share experience, and enhance collaborations among
researchers, professionals, and application developers in various
aspects of QoI, QoE, QoS for pervasive computing and crowdsensing in
network contexts including wireless, mobile and sensor networks.

Each accepted workshop paper requires a full PerCom registration (no
registration is available for workshops only)
Selected high quality papers will be considered for publication in the
Elsevier's Pervasive and Mobile Computing (PMC) journal.

Important Dates
Paper submission deadline - November 11 December 2, 2019

Acceptance notification - December 20, 2019

Camera ready due - January 31, 2020

http://www.cs.unibo.it/projects/iq2s-2020/

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