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Traffic modeling for Machine-to-Machine (M2M) last mile wireless access networks

机译:机器对机器(M2M)最后一英里无线访问网络的流量建模

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The most challenging issue in Machine-to-Machine (M2M) last mile wireless access networks is the management of a large number of M2M devices that generate a vast amount of M2M traffic. The communications traffic for various M2M applications or services is classified as Fixed-Scheduling (FS) or Event-Driven (ED). The FS traffic is an operational traffic, which occurs on a periodic basis, such as reports on the measured data, sent by M2M sensor devices. The ED traffic, which is assumed to have a higher priority, is triggered by occurrence of specific events, such as the traffic generated by M2M devices, due to failure in the monitored systems. To date, we have not seen any traffic model for M2M last mile wireless access networks, which incorporates the different characteristics of ED and FS traffic. Thus, in this paper, we develop an analytical traffic model for M2M last mile wireless access networks based on a priority queuing system, which considers the combination of both periodic FS and random ED traffic. By using the proposed model, we derive expressions for the mean queuing delay and blocking probability of each traffic class. The derived analytical expressions are validated by simulations of a wireless network model and are shown to agree very well.
机译:机器对机器(M2M)的最后一英里无线访问网络中最具挑战性的问题是对大量生成大量M2M流量的M2M设备的管理。各种M2M应用程序或服务的通信流量分为固定调度(FS)或事件驱动(ED)。 FS流量是一种操作流量,它定期发生,例如M2M传感器设备发送的有关测量数据的报告。由于受监视系统的故障,特定事件的发生(例如M2M设备生成的通信量)触发了ED通信量(假定具有更高的优先级)。迄今为止,我们还没有看到M2M最后一英里无线接入网的任何流量模型,该模型融合了ED和FS流量的不同特征。因此,在本文中,我们基于优先级排队系统开发了M2M最后一英里无线访问网络的分析流量模型,该模型考虑了周期性FS和随机ED流量的组合。通过使用提出的模型,我们得出了每个流量类别的平均排队延迟和阻塞概率的表达式。通过无线网络模型的仿真验证了得出的解析表达式,并显示出很好的一致性。

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