ABSTRACT

To appear in the 3rd International Workshop on Self-adaptive and Autonomic Computing Systems. Copenhagen, Denmark, August 2005. Supercedes Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-05-101, February 2005.

Towards self-predicting systems: What if you could ask “what-if”?

Eno Thereska, Dushyanth Narayanan*, Gregory R. Ganger

Parallel Data Laboratory, Carnegie Mellon University.
Pittsburgh, PA 15213

* Microsoft Research, UK

http://www.pdl.cmu.edu/

Today, management and tuning questions are approached using if...then... rules of thumb. This reactive approach requires expertise regarding of system behavior, making it difficult to deal with unforeseen uses of a system’s resources and leading to system unpredictability and large system management overheads. We propose a What...if... approach that allows interactive exploration of the effects of system changes, thus converting complex tuning problem into simpler search problems. Through two concrete management problems, automating system upgrades and deciding on service migrations, we identify system design changes that enable a system to answer What...if... questions about itself.

KEYWORDS: self-predicting, system upgrades, service migration

FULL PAPER (CONFERENCE VERSION): pdf
FULL PAPER (TR VERSION): pdf / postscript