Performance evaluation and analysis of a discrete queue system with multiple working vacations and non-preemptive priority

Ma, Zhanyou; Wang, Wenbo; Hu, Linmin

doi:10.3934/jimo.2018196

Cited by 2 publications

(1 citation statement)

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“…Xu et al [12] analyzed the multi-server working vacation queueing system with negative customers, its QBD process and generating matrix were derived from the multiple vacation model, and then the steady-state distribution expression of the system queue length and certain system indicators were given by using the matrix-geometric solution method. Ma et al [13] studied the discrete working vacation queue with non-preemptive priority and variable service rate, gave the stationary distribution of the system and analyzed the equilibrium behavior of two types of customers. Wang et al [14] established a synchronous multiple vacation queueing model based on the sleep mechanism of the standby module and studied a MEC task offloading strategy incorporating virtual machine clustering and sleep mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of P2p network content delivery based on queueing model

Ma,

Yan,

Wang

et al. 2023

Cluster Comput

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In P2P networks, content delivery is very critical, but there are not many relevant research results. In this paper, in order to simulate content delivery in P2P mode, online players are abstracted as servers that can provide services, the peers write content to buffer is abstracted as the customers' arrival, and the players read content from buffer is abstracted as the service process of the servers. An M/M/c queueing model with random variation in the number of servers is developed considering the influence of the number of P2P online servers on energy consumption, and negative customer and preemptive priority policies are introduced. The matrix-geometric solution method was used to derive performance measures for two types of customer, such as average queue length and average delay in the steady state of the system. And use Matlab to give some numerical examples to analyze the trend of performance measures with parameters in P2P networks. The benefit function is established to obtain the parameter values that make the social benefit optimal by Nash equilibrium and social optimal strategy.

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Section: Introductionmentioning

confidence: 99%