Study of a Controllable Queueing System with Unreliable Heterogeneous Servers

Efrosinin, Dmitry; Farkhadov, Mais; Stepanova, Natalia

doi:10.1134/s0005117918020066

Cited by 8 publications

(2 citation statements)

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“…This paper proposes a more flexible system that allows for the selection of a new number of allocated resources depending on the network load. To address this issue, we utilized controllable queuing systems [51][52][53].…”

Section: Our Previous Workmentioning

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: Our Previous Workmentioning

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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“…Neuts and Takahashi 31 explored that QS with more than two heterogeneous servers is intractable to get an analytical result. Efrosinin et al 32 analysed the reliability of QS with two unreliable heterogeneous servers, where the effects of some parameters are explored.…”

Section: Introductionmentioning

confidence: 99%

Reliability analysis and selective maintenance for multistate queueing system

Tang

Jia

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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The reliability theory of the multi-state system (MSS) has received considerable attention in recent years, as it is able to characterize the multi-state property and complicated deterioration process of systems in a finer way than that of binary-state system. In general, the performance of the task processing type MSS is typically measured by an operation time (processing speed). Whereas, considering the queueing phenomenon caused by the random arrival and processing of tasks, some other criteria should be taken into account to evaluate the quality of service (QoS) and the profit of stakeholders, such as waiting time, service and abandon rate of tasks and consequent profit rate. In this article, we focus on the queueing process of tasks and analyse the performance and reliability of MSS in an M/M/2 queueing model, which is referred to as a multi-state queueing system (MSQS). Two kinds of deterioration are studied including the gradual degradation of servers and the sudden breakdown of the whole system. A performance assessment function is defined to obtain the profit rate of MSQS in different performance states. Based on the proposed performance function, the selective maintenance method is studied to optimize the accumulated profit under the constraint of maintenance resource and time.

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