TY - JOUR
T1 - Predictability of Process Resource Usage
T2 - A Measurement-Based Study on UNIX
AU - Devarakonda, Murthy V.
AU - Iyer, Ravishankar K.
N1 - Funding Information:
Manuscript received February 12, 1988; revised July 5, 1989. Recommended by W. Royce. This work was supported by the National Aeronautics and Space Administration under NASA Grant NAG-1.613.
PY - 1989/12
Y1 - 1989/12
N2 - This paper develops a statistical approach for predicting the CPU time, the file I/O, and the memory requirements of a program at the beginning of its life, given the identity of the program. Initially, statistical clustering is used to identify high-density regions of process resource usage. The identified regions form the states for building a state-transition model to characterize the resource usage of each program in its past executions. The prediction scheme uses the knowledge of the program's resource usage in its last execution together with its state-transition model to predict the resource usage in its next execution. The prediction scheme is shown to work using process resource-usage data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate strongly with the actual; the coefficient of correlation between the predicted and actual values for CPU time is 0.84. The errors in prediction are mostly small and are heavily skewed toward small values.
AB - This paper develops a statistical approach for predicting the CPU time, the file I/O, and the memory requirements of a program at the beginning of its life, given the identity of the program. Initially, statistical clustering is used to identify high-density regions of process resource usage. The identified regions form the states for building a state-transition model to characterize the resource usage of each program in its past executions. The prediction scheme uses the knowledge of the program's resource usage in its last execution together with its state-transition model to predict the resource usage in its next execution. The prediction scheme is shown to work using process resource-usage data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate strongly with the actual; the coefficient of correlation between the predicted and actual values for CPU time is 0.84. The errors in prediction are mostly small and are heavily skewed toward small values.
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U2 - 10.1109/32.58769
DO - 10.1109/32.58769
M3 - Article
AN - SCOPUS:0024884030
SN - 0098-5589
VL - 15
SP - 1579
EP - 1586
JO - IEEE Transactions on Software Engineering
JF - IEEE Transactions on Software Engineering
IS - 12
ER -