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首页> 外文期刊>Probability in the Engineering and Informational Sciences >FINDING EXPECTED REVENUES IN G-NETWORK WITH SIGNALS AND CUSTOMERS BATCH REMOVAL
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FINDING EXPECTED REVENUES IN G-NETWORK WITH SIGNALS AND CUSTOMERS BATCH REMOVAL

机译:通过信号和客户批量删除来查找G网络中的预期收入

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摘要

The paper provides an analysis of G-network with positive customers and signals when signals arriving to the system move customer to another system or destroy in it a group of customers, reducing their number to a random value that is given by a probability distribution. The signal arriving to the system, in which there are no positive customers, does not exert any influence on the queueing network and immediately disappears from it. Streams of positive customers and signals arriving to each of the network systems are independent. Customer in the transition from one system to another brings the latest some revenue, and the revenue of the first system is reduced by this amount. A method of finding the expected revenues of the systems of such a network has been proposed. The case when the revenues from transitions between network states are deterministic functions depending on its states has been considered. A description of the network is given, all possible transitions between network states, transition probabilities, and revenues from state transitions are indicated. A system of difference-differential equations for the expected revenues of network systems has been obtained. To solve it, we propose a method of successive approximations, combined with the method of series. It is proved that successive approximations converge to the stationary solution of such a system of equations, and the sequence of approximations converges to a unique solution of the system. Each approximation can be represented as a convergent power series with an infinite radius of convergence, the coefficients of which are related by recurrence relations. Therefore, it is convenient to use them for calculations on a PC. The obtained results can be applied in forecasting losses in information and telecommunication systems and networks from the penetration of computer viruses into it and conducting computer attacks.
机译:本文提供了对具有积极客户的G网络的分析,并在到达系统的信号将客户转移到另一个系统或在其中破坏一组客户时发出信号,从而将他们的数量减少到由概率分布给出的随机值。到达没有积极客户的系统的信号不会对排队网络​​产生任何影响,并立即从排队网络中消失。积极的客户流和到达每个网络系统的信号是独立的。从一个系统过渡到另一个系统的客户带来了一些最新收入,第一个系统的收入减少了这个数量。已经提出了一种找到这种网络的系统的预期收益的方法。已经考虑了当网络状态之间的转换产生的收入是取决于其状态的确定性函数时的情况。给出了对网络的描述,指出了网络状态之间的所有可能转换,转换概率以及状态转换的收益。已经获得了用于网络系统的预期收益的差分-微分方程系统。为了解决这个问题,我们提出了一种逐次逼近的方法,并与级数方法相结合。证明了逐次逼近收敛到该方程组的平稳解,并且逼近序列收敛到该系统的唯一解。每个近似可以表示为具有无限收敛半径的收敛幂级数,其系数与递归关系相关。因此,在PC上使用它们进行计算很方便。所得结果可用于预测信息和电信系统和网络中由于计算机病毒的渗透和进行计算机攻击而造成的损失。

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