基于Kth马尔可夫模型的预测机动性模型

F. Lassabe, P. Canalda, P. Chatonnay, F. Spies
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引用次数: 11

摘要

随着无线网络的大量到来,终端的移动性随着互联程度的提高而提高。随着新型移动多媒体业务的出现,出现了移动多媒体内容流等新问题。本文提出了一种基于马尔可夫模型的移动模型,特别是全k马尔可夫模型。我们提出了三种预测模型:k -过去模型、K-to-J过去模型及其改进、K-to-1过去*模型。这些都是解决流动模式的相关解决方案。我们首先用与室内WiFi定位系统相关的各种现实基准数据验证了我们的方法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PredictiveMobility Models based on Kth Markov Models
With the massive arrival of wireless networks, the mobility of the terminals increases with the interconnections. New problems, such as mobile multimedia content streaming, arise with the emergence of new mobile multimedia services. In this paper, we present a mobility model based on the Markov models, especially the all-Kth Markov model. We present three predictive models: the K-past model, the K-to-J past model and its improvement, the K-to-1 past* model. The whole are pertinent solutions to tackle mobility patterns. We validate our approach firstly with various realistic benchmarks on data related to indoor WiFi positioning systems
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