GAP: A General Approach to Quantitative Diagnosis of Performance Problems
Joseph L. Hellerstein
IBM Thomas J. Watson Research Center
Hawthorne, New York 10532
Email: hellers_AT_us.ibm.com
Abstract
Quantitative performance diagnosis (QPD) provides explanations that quantify
the impact of problem causes. An example of such an explanation is "Increased web
server traffic accounts for 90% of the increase in LAN utilization, which in turn
accounts for 20% of the increase in web response times." This paper describes GAP,
a general approach to quantitative performance diagnosis. GAP has two parts: (1)
an algorithm for computing quantitative performance diagnoses and (2) a framework
for constructing diagnostic techniques that provides the basis for quantifications
produced by the algorithm. The GAP algorithm makes use of a measurement navigation
graph (MNG), a directed acyclic graph whose nodes are measurement variables and
whose arcs have weights that quantify the effect of child variables (e.g., LAN
utilization) on parent variables (e.g., response time). The framework for
developing diagnostic techniques consists of (a) the choice of statistic (e.g.,
mean, variance) to aggregate problem values and (b) the estimator of the statistic.
Keywords: problem determination
JNSM: Vol. 11, No. 2, 2003
GAP: A General Approach to Quantitative Diagnosis of Performance Problems [Vol. 11, No. 2, 2003]
NOTE: only abstract of paper available on-line; please contact your library or the authors for the full paper
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