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M/M/1 Retrial Queueing System with Negative Arrival under Pre-emptive Priority Service

机译:抢先优先服务下负到达的M / M / 1重试排队系统

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Consider a single server retrial queueing system with negative arrival under pre-emptive priority service in which three types of customers arrive in a Poisson process with arrival rate λ_1 for low priority customers and λ_2 for high priority customers and λ_3 for negative arrival. Low and high priority customers are identified as primary calls. Further assume that the service times follow an exponential distribution with parameters μ_1 and μ_2 for low and high priority customers. The retrial and negative arrivals are introduced for low priority customers only. Gelenbe (1991) has introduced a new class of queueing processes in which customers are either Positive or Negative. Positive means a regular customer who is treated in the usual way by a server. Negative customers have the effect of deleting some customer in the queue. In the simplest version, a negative arrival removes an ordinary positive customer or a random batch of positive customers according to some strategy. It is noted that the existence of a flow of negative arrivals provides a control mechanism to control excessive congestion at the retrial group and also assume that the negative customers only act when the server is busy. Let K be the maximum number of waiting spaces for high priority customers in front of the service station. The high priorities customers will be governed by the Pre-emptive priority service.We assume that the access from orbit to the service facility is governed by the classical retrial policy. This model is solved by using Matrix geometric Technique.Numerical study have been done for Analysis of Mean number of low priority customers in the orbit (MNCO), Mean number of high priority customers in the queue (MPQL), Truncation level (OCUT), Probability of server free and Probabilities of server busy with low and high priority customers for various values of λ_1, λ_2, λ_3, μ_1 μ_2, δ and k in elaborate manner and also various v particular cases of this model have been discussed.
机译:考虑在抢先优先服务下具有否定到达的单个服务器重试排队系统,其中三种类型的客户以泊松过程到达,其中低优先级客户的到达率为λ_1,高优先级客户的到达率为λ_2,否定到达的λ_3。低优先级和高优先级客户被标识为主呼叫。进一步假设对于低优先级和高优先级客户,服务时间遵循参数μ_1和μ_2的指数分布。重试和否定到达仅针对优先级较低的客户。 Gelenbe(1991)引入了一种新的排队过程,其中客户是肯定的还是否定的。积极是指由服务器按常规方式对待的常规客户。负面客户会删除队列中的某些客户。在最简单的版本中,否定到达会根据某种策略除去普通的积极客户或随机一批积极客户。应当指出,否定到达流的存在提供了一种控制机制,以控制重试组中的过度拥塞,并且还假定了否定客户仅在服务器繁忙时采取行动。令K为服务站前高优先级客户的最大等待空间数。高优先级客户将受到先占优先服务的约束。我们假设从轨道到服务设施的访问受经典的重试策略约束。通过使用矩阵几何技术解决了该模型。已经进行了数值研究,以分析轨道中低优先级客户的平均数量(MNCO),队列中高优先级客户的平均数量(MPQL),截断级别(OCUT),详尽讨论了λ_1,λ_2,λ_3,μ_1μ_2,δ和k的各种值时,无服务器的概率和低优先级和高优先级客户忙的服务器的概率,并且还讨论了该模型的各种特殊情况。

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