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CSMA networks in a many-sources regime: A mean-field approach

机译:多源体制下的CSMA网络:均值场方法

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With the rapid advance of the Internet of Everything, both the number of devices and the range of applications that rely on wireless connectivity show huge growth. Driven by these pervasive trends, wireless networks grow in size and complexity, supporting immense numbers of nodes and data volumes, with highly diverse traffic profiles and performance requirements. While well-established methods are available for evaluating the throughput of persistent sessions with saturated buffers, these provide no insight in the delay performance of flows with intermittent packet arrivals. The occurrence of empty buffers in the latter scenario results in a complex interaction between activity states and packet queues, which severely complicates the performance analysis. Motivated by these challenges, we develop a mean-field approach to analyze buffer contents and packet delays in wireless networks in a many-sources regime. The mean-field behavior simplifies the analysis of a large-scale network with packet arrivals and buffer dynamics to a low-dimensional fixed-point calculation for a network with saturated buffers. In particular, the analysis yields explicit expressions for the buffer content and packet delay distribution in terms of the fixed-point solution. Extensive simulation experiments demonstrate that these expressions provide highly accurate approximations, even for a fairly moderate number of sources.
机译:随着万物互联的飞速发展,依赖无线连接的设备数量和应用范围都显示出巨大的增长。在这些普遍趋势的驱动下,无线网络的规模和复杂性不断增长,支持数量众多的节点和数据量,并具有高度多样化的流量配置文件和性能要求。尽管已经建立了完善的方法来评估具有饱和缓冲区的持久会话的吞吐量,但是这些方法无法提供具有间歇性数据包到达的流的延迟性能。在后一种情况下,空缓冲区的出现导致活动状态和数据包队列之间的复杂交互,从而使性能分析严重复杂化。受这些挑战的驱使,我们开发了一种均值方法来分析多源方案中无线网络中的缓冲区内容和数据包延迟。平均场行为简化了对具有数据包到达和缓冲区动态的大规模网络的分析,从而简化了具有饱和缓冲区的网络的低维定点计算。尤其是,该分析根据定点解决方案给出了缓冲区内容和数据包延迟分布的明确表达式。大量的仿真实验表明,即使对于相当数量的源,这些表达式也提供了高度精确的近似值。

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