Parallel and Distributed Processing Symposium, International (2008)
Miami, FL, USA
Apr. 14, 2008 to Apr. 18, 2008
Sean Callanan , Stony Brook University, USA
Daniel J. Dean , Stony Brook University, USA
Michael Gorbovitski , Stony Brook University, USA
Radu Grosu , Stony Brook University, USA
Justin Seyster , Stony Brook University, USA
Scott A. Smolka , Stony Brook University, USA
Scott D. Stoller , Stony Brook University, USA
Erez Zadok , Stony Brook University, USA
In this paper, we introduce the new technique of High-Confidence Software Monitoring (HCSM), which allows one to perform software monitoring with bounded overhead and concomitantly achieve high confidence in the observed error rates. HCSM is formally grounded in the theory of supervisory control of finite-state automata: overhead is controlled, while maximizing confidence, by disabling interrupts generated by the events being monitored — and hence avoiding the overhead associated with processing these interrupts-for as short a time as possible under the constraint of a user-supplied target overhead O<inf>target</inf>. HCSM is a general technique for software monitoring in that HCSM-based instrumentation can be attached at any system interface or API. A generic controller implements the optimal control strategy described above. As a proof of concept, and as a practical framework for software monitoring, we have implemented HCSM-based monitoring for both bounds checking and memory leak detection. We have further conducted an extensive evaluation of HCSM’s performance on several real-world applications, including the Lighttpd Web server, and a number of special-purpose micro-benchmarks. Our results demonstrate how confidence grows in a monotonically increasing fashion with the target overhead, and that tight confidence intervals can be obtained for each target-overhead level.
R. Grosu et al., "Software monitoring with bounded overhead," 2008 IEEE International Parallel & Distributed Processing Symposium(IPDPS), Miami, FL, 2008, pp. 1-8.