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Queue Analysis and Multiplexing of Heavy-tailed Traffic in Wireless Packet Data Networks

机译:无线分组数据网络中重尾流量的队列分析和多路复用

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摘要

Recent research based on traffic measurements shows that Internet traffic flows have a fractal nature (i.e., self-similarity property), which causes an underestimation of network engineering parameters when using the conventional Poisson model. Preliminary field measurements demonstrate that packet data traffic in wireless communications also exhibits self-similarity. In this paper, we investigate the queuing behavior of self-similar traffic flows for data applications in a packet-switching single-server wireless network. The traffic is generated by an on-off source with heavy-tailed on periods and exponentially distributed off periods. We extend previous analysis of a relation among the asymptotic distribution of loss probability, traffic specifications, and transmission rate for a wireline system to a wireless system, taking into account wireless propagation channel characteristics. We also investigate the multiplexing of heavy-tailed traffic flows with a finite buffer for the downlink transmission of a wireless network. Computer simulation results demonstrate that assumptions made in the theoretical analysis are reasonable and the derived relationships are accurate.
机译:基于流量测量的最新研究表明,互联网流量具有分形性质(即自相似性),这在使用常规Poisson模型时会导致网络工程参数的低估。初步现场测量表明,无线通信中的分组数据流量也表现出自相似性。在本文中,我们研究了数据包交换单服务器无线网络中数据应用的自相似流量的排队行为。流量是由开-关源生成的,该开-关源具有重尾的开启时间段和呈指数分布的关闭时间段。考虑到无线传播信道的特性,我们将先前的损失概率的渐近分布,流量规范和有线系统到无线系统的传输速率之间的关系的分析扩展了下来。我们还研究了用于无线网络下行链路传输的带有有限缓冲区的重尾业务流的复用。计算机仿真结果表明,理论分析中的假设是合理的,推导的关系是准确的。

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