Discrete and Continuous Models and Applied Computational Science (Dec 2021)

To analysis of a two-buffer queuing system with cross-type service and additional penalties

  • Irina A. Kochetkova,
  • Anastasia S. Vlaskina,
  • Dmitriy V. Efrosinin,
  • Abdukodir A. Khakimov,
  • Sofiya A. Burtseva

DOI
https://doi.org/10.22363/2658-4670-2021-29-2-158-172
Journal volume & issue
Vol. 29, no. 2
pp. 158 – 172

Abstract

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The concept of cloud computing was created to better preserve user privacy and data storage security. However, the resources allocated for processing this data must be optimally allocated. The problem of optimal resource management in the loud computing environment is described in many scientific publications. To solve the problems of optimality of the distribution of resources of systems, you can use the construction and analysis of QS. We conduct an analysis of two-buffer queuing system with cross-type service and additional penalties, based on the literature reviewed in the article. This allows us to assess how suitable the model presented in the article is for application to cloud computing. For a given system different options for selecting applications from queues are possible, queue numbers, therefore, the intensities of transitions between the states of the system will change. For this, the system has a choice policy that allows the system to decide how to behave depending on its state. There are four components of such selection management models, which is a stationary policy for selecting a queue number to service a ticket on a vacated virtual machine each time immediately before service ends. A simulation model was built for numerical analysis. The results obtained indicate that requests are practically not delayed in the queue of the presented QS, and therefore the policy for a given model can be considered optimal. Although Poisson flow is the simplest for simulation, it is quite acceptable for performance evaluation. In the future, it is planned to conduct several more experiments for different values of the intensity of requests and various types of incoming flows.

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