GMU Software Engineering
Seminar Series
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Date: Mon, 11/09/2009
Time: 12 – 1pm
Location: 4201 Engineering
Food: Pizza & Soda
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Title: Architectural Patterns for Decentralized Self-Adaptive Systems
Speaker: Danny Weyns
Abstract
Self-adaptability has been proposed as an effective approach to tackle the
increasing complexity of constructing and managing contemporary software
systems. Self-adaptability endows a system with the capability to adapt itself
to changes in its environment and user requirements. Several researchers have
argued that software architecture provides the right level of abstraction and
generality to deal with the challenges of self-adaptability. One of the major
challenges in self-adaptive systems is dealing with distribution and
decentralization. Decentralized control is crucial for quality requirements
such as openness and scalability. Over the past 8 years, we have been studying
decentralized architectures for realizing self-adaptability based on
multi-agent systems (MAS). A MAS architecture structures the software in a
number of interacting autonomous entities (agents) that cooperatively realize
the system goals. Agents flexibly adapt their behavior and interactions to
dynamics in the system or its environment. In the course of designing and
building various MAS applications, we derived several architectural patterns
that provide generic solution schemes for recurring design problems. In this
talk, I will zoom in on a number of these patterns and illustrate them with
practical examples.
Bio
Danny Weyns is a post-doctoral researcher at the Katholieke Universiteit
Leuven, Belgium. His main research interests are in software architecture,
self-adaptive systems, multi-agent systems, and middleware for decentralized
systems. Danny is currently visiting researcher at Valoria Lab of the
Université de Bretagne-Sud, France where he works with Prof. Flavio Oquendo on
formal modeling of dynamic software architectures of decentralized systems.
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Title: Continuous Learning for Self-Adaptive Software Systems
Speaker: Jesper Andersson
Abstract
Recent
computing trends, such as pervasiveness and mobility of systems, increase the
software complexity to a point where the software itself must adapt at
run-time. In order to meet functional and quality requirements in a setting of
ever changing conditions and constraints, self-adaptation is one possible
answer. Adaptive system design, development, and maintenance add additional
challenges for software engineers. In addition to the complexity of static
system engineering, systems must know when to adapt, where to adapt, and how to
adapt. Acquiring knowledge to answer these questions is a challenging task and
the problem becomes even more complex as the systems, and number of conditions
and constraints grow. In this talk we present and exemplify work in progress on
a dual learning process with architecture support that combines off-line and
on-line mechanisms. Off-line, the system is simulated or subject for controlled
executions. The collected information is used to derive configuration
knowledge, i.e., configuration rules. We realize that off-line learning will
never be 100% correct or complete in the general case. We address this issue by
employing on-line learning strategies for gradually tuning/extending/replacing
configuration knowledge.
Bio
Jesper Andersson is an assistant professor at Växjö University in Sweden. His
main research interests are in software architectures, end-user programming and
reuse for self adaptive systems development and self adaptation in distributed
architectures.
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Sam Malek, Ph.D.
Assistant Professor
Department of Computer Science
Volgenau School of Information Technology and Engineering
George Mason University
Fairfax, VA 22030-4444 U.S.A.
Phone: +1-703-993-1677
Email: [log in to unmask]
WWW: http://www.cs.gmu.edu/~smalek/