To efficiently manage resources and provide guaranteed services, today's computing systems monitor and collect a large number of resource usages, for example the average and time series of CPU utilization. However, little is known about the analytical distribution of resource usages, which are the crucial parameters to infer performance metrics defined in service level agreements (SLAs), such as response times and throughputs. In this paper, we aim to characterize the entire distribution of CPU utilization via stochastic reward models. In particular, we first study and derive the probability density function of the utilization of widely known and applied queuing systems, namely Poisson processes, Markov modulated Poisson processes and time-varying Poisson processes. Secondly, we apply our proposed analysis on characterizing the CPU usage of live production systems, and simulated queuing systems. Evaluation results show that analytical characterization of the selected queueing models can capture the utilization distribution of a wide range of real-life systems well, and we argue the robustness of our methodology to further infer system performance metrics

Characterization Analysis of Resource Utilization Distribution

GRIBAUDO, MARCO;PIAZZOLLA, PIETRO
2013

Abstract

To efficiently manage resources and provide guaranteed services, today's computing systems monitor and collect a large number of resource usages, for example the average and time series of CPU utilization. However, little is known about the analytical distribution of resource usages, which are the crucial parameters to infer performance metrics defined in service level agreements (SLAs), such as response times and throughputs. In this paper, we aim to characterize the entire distribution of CPU utilization via stochastic reward models. In particular, we first study and derive the probability density function of the utilization of widely known and applied queuing systems, namely Poisson processes, Markov modulated Poisson processes and time-varying Poisson processes. Secondly, we apply our proposed analysis on characterizing the CPU usage of live production systems, and simulated queuing systems. Evaluation results show that analytical characterization of the selected queueing models can capture the utilization distribution of a wide range of real-life systems well, and we argue the robustness of our methodology to further infer system performance metrics
2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems
9780769551029
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/824356
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact