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Discord model for detecting unexpected demands in mobile networks

机译:用于检测移动网络中意外需求的Discord模型

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Predicting the number of calls in a cell in average must be an important issue in mobile computing. It is quite useful in performance modeling and usually assumed as a random Poisson value. For effective management of cellular networks, the average number of calls should be carefully traced and the unexpected changes in the numbers need to be promptly detected. In this paper, we propose an efficient algorithm detecting those changes in the behavior of users based on the technique proposed for point-of-change problem just in terms of the number of call arrivals. Computer simulation reveals the proposed method effectively detect the discord, and the developed model is very accurate that the difference is as small as mostly less than 1%.
机译:预测平均一个小区中的呼叫数量必须是移动计算中的重要问题。它在性能建模中非常有用,通常假定为随机泊松值。为了有效地管理蜂窝网络,应仔细跟踪平均呼叫数量,并且需要迅速检测出数量意外变化。在本文中,我们提出了一种有效的算法,该算法基于仅针对呼叫到达次数而针对变化点问题提出的技术来检测用户行为中的那些变化。计算机仿真表明,该方法可以有效地检测出不协调现象,并且所建立的模型非常准确,差异很小,大部分小于1%。

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