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Cyber Physical Computing
Department of Computer Science
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Cyber Physical Computing Computer Science
has always been an application-oriented discipline. Its greatest advances that
broadly altered the quality of life, such as the Internet, databases, and
supercomputers stemmed primarily from applications brought about by needs of
individuals, businesses, and the government. At present, an expanding
frontier for computer scientists lies at the intersection of the logical and
physical realms. As computing elements become embedded more pervasively in
our environment, a new cyber-physical fabric arises in which logical
processing is very deeply intertwined with the distributed physical
environment in which it occurs. Computing becomes less obtrusive and a more
natural part of the external world. It becomes more autonomous and less
reliant on human input, intervention, and administration. Physical objects
acquire new logical properties due to embedded computation, sensing, and
actuation. New applications arise that improve the quality of life (e.g.,
smart assisted living facilities), enhance social experiences and human
communication (e.g., new cyber-physical communication media), improve
accessibility of information (e.g., wide-area data services), and help
advance fundamental knowledge in many environmental, biological, and physical
disciplines. In this new realm,
computer science must be redefined. New models and paradigms are needed for
computation. New underlying theoretical foundations are needed to support
such paradigms. New programming languages and distributed middleware tools
must be developed around the emerging abstractions of cyber-physical
computation. Networking must be redefined to integrate myriads of physical
data sources, actuators, and computing elements, as well as to develop
appropriate application-layer data services. New operating systems are needed
that are optimized for the new computing realm, as opposed to the current
machine architectures and applications. Data mining and machine learning
techniques are needed to identify data patterns, learn context, and act
autonomously without human assistance.
The Cyber-Physical
Computing Group is a multidisciplinary team that investigates the
aforementioned aspects of tomorrow’s computing systems. Selected
Publications L.
Luo, T. Abdelzaher, T. He, and J. A. Stankovic, "EnviroSuite: An
Environmentally Immersive Programming Framework for Sensor Networks,"
Accepted to ACM
Transactions on Embedded Computing Systems (TECS), 2006. William
Hawkins and Tarek Abdelzaher, "Towards Feasible Region Calculus: An
End-to-end Schedulability Analysis of Real-Time Multistage Execution," IEEE Real-time Systems Symposium,
Tarek
F. Abdelzaher, Shashi Prabh, Raghu Kiran, "On Real-time Capacity Limits
of Multihop Wireless Sensor Networks," IEEE Real-time Systems Symposium, |
Research Themes A versatile collection
of new research directions are started in this group. On the analytic front,
new fundamental theory and models are sought for distributed computation.
Capacity limits are investigated to quantify fundamental tradeoffs between
time, space, and energy. On the
systems side, challenges are addressed in developing the next generation
middleware for cyber-physical applications. New protocols, compilers,
programming languages, and operating systems are needed. A categorization of
research directions is listed below.
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Sensor Networks: Today, hundreds of millions of
sensors are deployed in our environment. This includes cameras on myriads of
cell-phones, ubiquitous indoor temperature sensors, garage-door motion
sensors, web cams in public spaces, among others. Hardware miniaturization
and wireless communication advances suggest increased proliferation of
sensing devices and their integration into wireless sensor networks for
myriads of urban, military, social, and medical applications. Zigbee,
Bluetooth and other wireless technologies present possible options for the
interconnection of sensors. Research on sensor networks investigates network
protocols, services, resource management, and programming paradigms tailored
to the new environment. |
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Future
Internet Architecture: The Internet was born as a data communication medium,
yet it is being used increasingly for information retrieval. Such information
will typically originate from embedded sources. Human needs for bandwidth are
limited, since our capacity to source or sink information is bounded (e.g.,
by limits of sensory perception). Future growth in network bandwidth demand
will eventually come from embedded sources. Data collected from such sources
will need to be organized for efficient search, retrieval, and proactive
event detection. This suggests a fundamental re-thinking of the Internet
architecture around the concepts of data retrieval, as opposed to
point-to-point or multiparty communication. |
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Smart Attire: Our future wardrobe
is the next likely platform for embedded computing, after PDAs, cell phones,
and multimedia devices such as iPODs. A suite of human-centric software
applications will execute on the new platform. Research is needed into new
operating system abstractions, computing models, languages, and services
(such as support for security and privacy) in Smart Attire applications. This
project develops experimental prototypes of attire fitted with sensors,
microprocessors, and memory, using them as the vehicle to investigate the
aforementioned topics. |
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Environmentally
Immersive Programming: This project develops a new distributed
computing paradigm suitable for cyber-physical computing applications marked
by heavy interactions between the logical realm and the external environment.
The paradigm exports an address space that combines logical objects and
(addressable representations of) external physical objects in the same
“cyber-physical” space. |
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Feasible Region Calculus: This project
develops a fundamentally new theory for analysis of temporal and spatial
properties in open systems based on feasible regions. A calculus is developed
for composing the feasible regions of subsystems to generate those of the
overall application. Results applicable to the understanding of fundamental
capacity limits of new models of computation. |
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Software Predictability: The increasing
complexity and heterogeneity of future distributed embedded software systems
and the increasing sources of unpredictability that affect software
performance in the face of physical time and space constraints call for new
theory, architectural mechanisms, computing paradigms, and programming
abstractions to support predictable software behavior, analyzability, and
performance guarantees. In this group, we develop new analysis tools,
middleware, high-level interfaces, and underlying analytic foundations for
software predictability. Of particular interest is predictability of temporal
behavior, which is of special importance in real-time and embedded systems. |