Queue with Retrial Group for Modeling Best Effort Traffic with Minimum Bit Rate Guarantee Transmission Under Network Slicing

Markova, Ekaterina; Adou, Yves; Ivanova, Daria; Golskaia, Anastasia; Samouylov, Konstantin

doi:10.1007/978-3-030-36614-8_33

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…Mathematical methods commonly used to solve corresponding optimization problems include optimization theory for linear and nonlinear problems, game theory, cooperative game theory (Nash equilibrium), machine learning [37], MDP, continuous-time Markov chain (CTMC), and queuing theory. A retrial queuing system with an infinite orbit was proposed for analyzing prioritization schemes and resource reservation [38]. In another study [39], a resource queuing system with signals, where upon arrival, the signal interrupts a user to try again with a new bit-rate requirement, was analyzed.…”

Section: Resource Capacity Planningmentioning

confidence: 99%

Controllable Queuing System with Elastic Traffic and Signals for Resource Capacity Planning in 5G Network Slicing

Kochetkova,

Leonteva,

Ghebrial

et al. 2023

Future Internet

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Fifth-generation (5G) networks provide network slicing capabilities, enabling the deployment of multiple logically isolated network slices on a single infrastructure platform to meet specific requirements of users. This paper focuses on modeling and analyzing resource capacity planning and reallocation for network slicing, specifically between two providers transmitting elastic traffic, such during as web browsing. A controller determines the need for resource reallocation and plans new resource capacity accordingly. A Markov decision process is employed in a controllable queuing system to find the optimal resource capacity for each provider. The reward function incorporates three network slicing principles: maximum matching for equal resource partitioning, maximum share of signals resulting in resource reallocation, and maximum resource utilization. To efficiently compute the optimal resource capacity planning policy, we developed an iterative algorithm that begins with maximum resource utilization as the starting point. Through numerical demonstrations, we show the optimal policy and metrics of resource reallocation for two services: web browsing and bulk data transfer. The results highlight fast convergence within three iterations and the effectiveness of the balanced three-principle approach in resource capacity planning for 5G network slicing.

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Section: Resource Capacity Planningmentioning

confidence: 99%

Controllable Queuing System with Elastic Traffic and Signals for Resource Capacity Planning in 5G Network Slicing

Kochetkova,

Leonteva,

Ghebrial

et al. 2023

Future Internet

Self Cite

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“…The process describing the system' behavior is not reversible Markov process. Therefore, the stationary probability distribution q(n 1 , n 2 , s) (n1,n2,s)∈Y = q can be calculated using a numerical solution [13] of the equilibrium' equations system q • A = 0, q • 1 T = 1, where A is the infinitesimal generator of Markov process, elements a((n 1 , n 2 , s)(n 1 , n 2 , s )) of which are defined as follows:…”

Section: Numerical Solutionmentioning

confidence: 99%

“…Note that, model with limited storage capacities of buffer and its retrial group has already been investigated in [13], where a computed numerical solution of the equilibrium equations system was used to analyze the characteristics. However, for model to match reality, the storage capacities must be unlimited.…”

Section: Introductionmentioning

confidence: 99%

Methods for Analyzing Slicing Technology in 5G Wireless Network Described as Queueing System with Unlimited Buffer and Retrial Group

Adou

Markova

2021

Information Technologies and Mathematical Modelling. Queueing Theory and Applications

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Fourth generation wireless network was very soon about to not be able to support or withstand the exponential growth of traffic in modern wireless telecommunication networks. In addition, the inflexibility of mobile networks until now is making the situation even more complicated. In response, the fifth generation (5G) wireless telecommunication network was developed, allowing flexible and quick deployment of applications and services to accommodate specific requirements of users in very diverse fields. The cornerstone of 5G is called slicing technology: a mechanism making possible the creation and configuration of multiple network services on top of the same infrastructure with help of its defined network slices. The international telecommunication union (ITU) has defined three categories of use which have been brought into conformity with the 3GPP standards. These categories are specified by three generic slices of 5G: enhanced mobile broadband (eMBB), ultra-reliable low latency communications (uRLLc) and massive machine type communications (mMTC). We consider queueing system with queue and its retrial group for modeling slicing technology in 5G wireless network.

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“…So it is a combination and extension of the research conducted in [1,9,14,17]. In [9] the authors consider one of the potential radio resource allocation schemes for multiservice wireless networks with Network Slicing technology. They describe it by using the retrial queue with the orbit to wait for sessions.…”

Section: Introductionmentioning

confidence: 99%

Resource Queueing System for Analysis of Network Slicing Performance with QoS-Based Isolation

Moskaleva

Lisovskaya

Gaidamaka

2021

Information Technologies and Mathematical Modelling. Queueing Theory and Applications

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Network slicing is defined as one of the main components of fifth-generation mobile communications that can solve the problem of colossal growth in data volume traffic in cellular networks. A key feature of slicing is to limit the effect of one slice on another to provide a high quality of service. Therefore, in this paper, a model for resource sharing in slicing using the queueing theory methods is constructed. The main aim is to determine how radio resources should be fairly shared between different slices in the system. The proposed algorithm ensures the isolation of slices according to the quality of service. The resource sharing problem is formulated as an optimization problem. Analysis of the system's performance characteristics will allow us to conclude that the isolation parameter has a significant effect on metrics of interest.

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Queue with Retrial Group for Modeling Best Effort Traffic with Minimum Bit Rate Guarantee Transmission Under Network Slicing

Cited by 5 publications

References 10 publications

Controllable Queuing System with Elastic Traffic and Signals for Resource Capacity Planning in 5G Network Slicing

Controllable Queuing System with Elastic Traffic and Signals for Resource Capacity Planning in 5G Network Slicing

Methods for Analyzing Slicing Technology in 5G Wireless Network Described as Queueing System with Unlimited Buffer and Retrial Group

Resource Queueing System for Analysis of Network Slicing Performance with QoS-Based Isolation

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