DATE: Thursday, September 4, 2003
TIME: Noon - 1 pm
PLACE: Newell-Simon Hall 3305

Jeff Kephart
IBM Thomas J. Watson Research Center

Research Challenges of Autonomic Computing

The increasing complexity of computing systems is beginning to overwhelm the capabilities of software developers and system administrators to design, evaluate, integrate, and manage these systems. Major software and system vendors are concluding that the only viable long-term solution is to create computer systems that manage themselves, often referred to as autonomic computing systems.

I will describe how IBM Research is using a services-oriented architecture and a set of industry scenarios to coordinate a large, diverse autonomic computing research effort. Realizing the dream of autonomic computing will require meeting many significant challenges across a broad span of disciplines, including human-computer interaction (interfaces, policies, etc.), systems architecture, software engineering, problem localization and remediation, security, artificial intelligence (agents, learning, knowledge representation, negotiation, planning, etc.) and mathematics (optimization, emergent behavior, etc.). I will discuss several of these fundamental challenges in the hope of encouraging faculty members to address some of them, possibly in collaboration with researchers at IBM.

Jeffrey O. Kephart manages the Agents and Emergent Phenomena group at the IBM Thomas J. Watson Research Center and chairs IBM's Autonomic Computing Advisory Board. His research focuses on the application of analogies from biology and economics to massively distributed computing systems, particularly in the domains of autonomic computing, e-commerce, and antivirus technology. His research efforts on the design of a digital immune system and on economic software agents have been publicized in publications such as The Wall Street Journal, The New York Times, Forbes, Wired, Harvard Business Review, IEEE Spectrum, and Scientific American. Kephart received a BS from Princeton University and a PhD from Stanford University, both in electrical engineering.

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