12/3/2009 3:30pm-4:30pm ECCR 265
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An Open Source Platform for Pervasive Computing
University College Dublin
Pervasive and autonomic systems share many features in common: they are highly
adaptive, involve a large and dynamically-changing population of components and
services, must deal with a variety of sensors and information sources delivering
partial and uncertain results and must deliver an overall experience which is
simultaneously adaptive to changing context but stable enough to present a
predictable and scrutable service to users and other systems. Building systems
which meet these criteria is challenging, involves considerable infrastructural
development work, and requires the designer to understand a wide range of quite
subtle issues -- all of which interfere with the development of
application-level services.
To support developers of pervasive systems we designed and built
Construct.
Construct differs from other pervasive systems platforms in a number of key
respects. It is completely standards-based, using RDF as its data exchange
model and ZeroConf for resource discovery. It supports a knowledge-centric
model of interaction where clients' actions are driven by queries and triggers
about the context of the system. It uses gossiping to maintain a consistent
state across a distributed data structure, which maximises robustness and
scalability and avoids many problems with hot-spots and hot-paths in
communications. Finally, it treats all information sources uniformly as sensors
acting as inputs to uncertain reasoning algorithms.
Dr. Steve Neely
has been researching the construction and management of autonomous distributed
systems since 1998. His current interests include programming models for global
computation and architectures for capricious information systems. In particular:
pervasive and ubiquitous computing, peer-to-peer networking, autonomics, sensor
systems, context-awareness, location tracking, middleware, Web Services,
persistence, code/process migration, semistructured data, XML datasets,
data fusion and data provenance.
Hosted by Katie Siek.
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