Performance Analysis of Cloud Computing Centers Using M/G/m/m+r Queuing Systems

@article{Khazaei2012PerformanceAO,
  title={Performance Analysis of Cloud Computing Centers Using M/G/m/m+r Queuing Systems},
  author={Hamzeh Khazaei and Jelena V. Misic and Vojislav B. Mi{\vs}i{\'c}},
  journal={IEEE Transactions on Parallel and Distributed Systems},
  year={2012},
  volume={23},
  pages={936-943}
}
Successful development of cloud computing paradigm necessitates accurate performance evaluation of cloud data centers. As exact modeling of cloud centers is not feasible due to the nature of cloud centers and diversity of user requests, we describe a novel approximate analytical model for performance evaluation of cloud server farms and solve it to obtain accurate estimation of the complete probability distribution of the request response time and other important performance indicators. The… 
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368 Citations
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368 Citations

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References

SHOWING 1-10 OF 30 REFERENCES
Performance Analysis of Cloud Computing Centers
TLDR
An analytical model for performance evaluation of cloud server farms is described, and the manner in which important performance indicators such as request waiting time and server utilization may be assessed with sufficient accuracy is demonstrated.
Service Performance and Analysis in Cloud Computing
TLDR
In an effort to deliver QoS guaranteed services in such a computing environment, the relationship among the maximal number of customers, the minimal service resources and the highest level of services is found.
Performance evaluation of cloud service considering fault recovery
TLDR
Detailed research is conducted on performance evaluation of cloud service considering fault recovery and the commonly adopted assumption of Poisson arrivals of users’ service requests is relaxed, and the interarrival times of service requests can take arbitrary probability distribution.
Approximations of the Mean Waiting Time in an M/G/s Queueing System
TLDR
In order to obtain mean waiting time approximations it appears to be useful to introduce a quantity (the “normed cooperation coefficient”) which is inversely proportional to WGs andWhich is in some sense a measure for the “cooperation” between the servers of the service facility.
M/G/c/K blocking probability models and system performance
Approximation of the Mean Queue Length of an M/G/c Queueing System
TLDR
Numerical results show that the approximation is accurate even when the coefficient of variation of the service time and the number of channels of the system are as large as 20 and 200, respectively.
Cloud Computing: a Perspective Study
TLDR
This paper brings an introductional review on the Cloud computing and provides the state-of-the-art of Cloud computing technologies.
Approximations for the M/G/m Queue
TLDR
A simple approximation for the queue length distribution of the M/G/m queue with finite waiting room is proposed and some numerical results indicate that the proposed approximation is rather accurate.
Optimal buffer design of an m/g/s queue with finite capacity ∗
This paper provides an approximate solution of a buffer design problem in an M/G/s queueing system with finite waiting spaces. The buffer design problem is to determine the smallest buffer capacity…
Approximations for the steady-state probabilities in the M/G/c queue
For the multi-server queue with Poisson arrivals and general service times we present various approximations for the steady-state probabilities of the queue size. These approximations are computed…
...
...