A Queueing System with Erlang Incoming Flow and Relative Priority

1978 ◽  
Vol 22 (4) ◽  
pp. 841-846
Author(s):  
V. G. Ushakov
Cybernetics ◽  
1975 ◽  
Vol 10 (2) ◽  
pp. 301-304
Author(s):  
I. A. Pogosyan ◽  
A. I. Klimenko

Author(s):  
Thomas C. Berg

By now, it is a commonplace of the American religious scene that the majority of the nation's white Protestant Christians are split into “two parties.” The ideological dividing line runs between “mainline” denominations—Methodists, Presbyterians, Episcopalians—and a bevy of conservative denominations and groups, but it also cuts through the mainline itself, which contains a substantial contingent of conservatives.Among the two parties' numerous disagreements, theological and political, few have run deeper and longer than their difference over the meaning and importance of evangelism, the activity of “proclaiming the gospel” to those outside the Christian community. Is the church's prime call in this regard to seek conversions to the Christian faith, or is it to show the love of Christ by working for charitable goals and social justice? A well-known 1973 study of Presbyterian clergy found that the greatest polarization between self-described “conservatives” and “liberals” came over the relative priority of evangelism and social action. Indeed, the fight over these goals was an important (though by no means the only) factor precipitating the “split” early in this century.


2017 ◽  
Vol 20 (7) ◽  
pp. 607-618 ◽  
Author(s):  
Yifei Wu ◽  
Zhengping Zou ◽  
Chao Fu ◽  
Weihao Zhang

Author(s):  
Viktor Afonin ◽  
Vladimir Valer'evich Nikulin

The article focuses on attempt to optimize two well-known Markov systems of queueing: a multichannel queueing system with finite storage, and a multichannel queueing system with limited queue time. In the Markov queuing systems, the intensity of the input stream of requests (requirements, calls, customers, demands) is subject to the Poisson law of the probability distribution of the number of applications in the stream; the intensity of service, as well as the intensity of leaving the application queue is subject to exponential distribution. In a Poisson flow, the time intervals between requirements are subject to the exponential law of a continuous random variable. In the context of Markov queueing systems, there have been obtained significant results, which are expressed in the form of analytical dependencies. These dependencies are used for setting up and numerical solution of the problem stated. The probability of failure in service is taken as a task function; it should be minimized and depends on the intensity of input flow of requests, on the intensity of service, and on the intensity of requests leaving the queue. This, in turn, allows to calculate the maximum relative throughput of a given queuing system. The mentioned algorithm was realized in MATLAB system. The results obtained in the form of descriptive algorithms can be used for testing queueing model systems during peak (unchanged) loads.


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