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Efficient quality of service-aware packet chunking scheme for machine-to-machine cloud services

机译:机器对机器云服务的有效的服务感知质量分组分割方案

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With the recent advances in machine-to-machine communications, huge numbers of devicesrnhave become connected and massive amounts of traffic are exchanged. Machine-to-machinernapplications typically generate small packets, which can profoundly affect the network performance.rnNamely, even if the packet arrival rate at the router is lower than the link bandwidth,rnbits per second, it can exceed the router forwarding capacity,which indicates the maximum numberrnof forwarded packets per second. This will cause the decrease in the network throughput.rnTherefore, eliminating the packets per second limitation by chunking small packets will enablernmachine-to-machine cloud services to spread further. This paper proposes new packet-chunkingrnschemes aimed at meeting both application requirements and improving achievable routerrnthroughput. In our schemes, multiple buffers, each of which accommodates packets classifiedrnbased on their delay requirement, are installed in parallel. Herein, we report on analysis of therntheoretically performance of these schemes, which enabled us to derivesomeimportant features.rnWe also propose a scheme whereby a single chunking buffer and parallel multiple buffers werernarranged in tandem. Through our simulation and numerical results, we determined that thesernschemes provide excellent performance in reducing the number of outgoing packets from thernrouter while meeting various delay requirements.
机译:随着机器对机器通信的最新发展,已经连接了大量的设备并且交换了大量的流量。机器对机器的应用程序通常会生成小的数据包,这会严重影响网络性能。即,即使路由器中的数据包到达速率低于链路带宽(每秒rnbits),也可能超过路由器的转发能力,这表明每秒转发的最大数据包数。因此,通过对小数据包进行分块来消除每秒的数据包限制将使机器对机器的云服务能够进一步传播。本文提出了一种新的数据包分块方案,旨在同时满足应用需求和提高可实现的路由器吞吐量。在我们的方案中,并行安装了多个缓冲区,每个缓冲区可容纳根据其延迟要求分类的数据包。本文中,我们报告了对这些方案的理论性能的分析,这使我们能够得出一些重要的特征。我们还提出了一种方案,其中将单个组块缓冲区和并行的多个缓冲区串联排列。通过我们的仿真和数值结果,我们确定了这些方案在减少来自路由器的传出数据包的数量的同时提供了出色的性能,同时满足了各种延迟要求。

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