# 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…

## 368 Citations

Resource Allocation in Cloud Computing with M/G/s- Queueing System

- Computer Science
- 2014

This model was used in order to evaluate the performance analysis of cloud server farms and it was solved to obtain accurate estimation of the complete probability distribution of the request response time and other important performance indicators.

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- Computer Science
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This paper provides new approximate formulas to compute the transition-probability matrix of this queuing system and compute the steady-state probabilities and some performance indicators such as blocking probability, mean response time, probability of immediate service and delay probability.

MMPP/G/m/m+r Queuing System Model to Analytically Evaluate Cloud Computing Center Performances

- Computer Science
- 2014

An approximate analytical model based on an approximate Markov chain model for performance evaluation of a cloud computing center is reported, based on queuing theory, a MMPP task arrivals, a general service time for requests as well as large number of physical servers and a finite capacity.

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- Computer Science
- 2014

This model is used to evaluate the performance analysis of cloud server frames and gets an accurate estimate of the complete probability distribution of the request response time and other important performance indicators such as: the mean number of tasks in the system, the distribution of waiting time, the probability of immediate service and the blocking probability.

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- Computer Science
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This paper surveys various works and models used to investigating the data center performance and evaluation of quality of service in iaas cloud computing systems and discusses the comparison between all the works as well as the system performance in terms of utilization, availability, waiting time and responsiveness.

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- Computer ScienceVECoS
- 2016

A new approximate analytical model is proposed in order to evaluate the performance of cloud computing center using M/G/c/c+ r queuing system and combines two models, a transform-based analytical model and an approximate Markov chain.

Performance Analysis of web Application deployment on cloud using M/M/S/K Queueing model

- Computer Science, Business
- 2018

The performance measures end-to-end response time, utilization of computing resources consumed, blocking probability, average time spent in the system and average waiting time in the queue are considered to evaluate the dynamic nature of the model.

A Fine-Grained Performance Model of Cloud Computing Centers

- Computer ScienceIEEE Transactions on Parallel and Distributed Systems
- 2013

This paper employs both the analytical and simulation modeling to addresses the complexity of cloud computing systems to obtain important performance metrics such as task blocking probability and total waiting time incurred on user requests.

Performance Analysis of Cloud Centers under Burst Arrivals and Total Rejection Policy

- Computer Science2011 IEEE Global Telecommunications Conference - GLOBECOM 2011
- 2011

A new approximate analytical model is described for performance evaluation of cloud server farms under burst arrivals and solved to obtain important performance indicators such as mean request response time, blocking probability, probability of immediate service and probability distribution of number of tasks in the system.

Performance Analysis of Cloud Computing Centers Serving Parallelizable Rendering Jobs Using M/M/c/r Queuing Systems

- Computer Science2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)
- 2017

This paper proposes an approximate analytical model that can guide cloud operators to determine a proper setting, such as the number of servers, the buffer size and the degree of parallelism, for achieving specific performance levels.

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