首页> 外文期刊>Computer networks >Adaptive congestion control framework and a simple implementation on high bandwidth-delay product networks
【24h】

Adaptive congestion control framework and a simple implementation on high bandwidth-delay product networks

机译:自适应拥塞控制框架和在高带宽延迟产品网络上的简单实现

获取原文
获取原文并翻译 | 示例

摘要

As new link technologies and sub-networks proliferate and evolve, a large number of TCP variants have been developed for different types of the network environments. They can lead to major performance gains by taking advantage of local characteristics of the specific network. However, these TCP variants could not be automatically chosen according to the lower network environments. In this paper, we propose the ACCF, an adaptive congestion control framework, which can automatically transition among existing congestion control mechanisms according to the change of the network status. Then we perform a simple implementation of ACCF over the networks with high bandwidth-delay product (BDP). It can switch the congestion control approaches between the delay-based ones and the loss-based ones according to the network status. Extensive experiments are conducted based on network simulators as well as over real wired networks on different time periods of the day. For the simulation measures, the experimental results show that the performance of ACCF is significantly improved as compared to other state-of-the-art algorithms in term of throughput, fairness and TCP-friendliness. For the real network tests, the experimental results show that ACCF achieves speedup ratios up to 225.83% compared with average throughput of other TCP congestion control algorithms.
机译:随着新的链接技术和子网的激增和发展,已经针对不同类型的网络环境开发了许多TCP变体。通过利用特定网络的本地特性,它们可以带来主要的性能提升。但是,无法根据较低的网络环境自动选择这些TCP变体。在本文中,我们提出了一种自适应拥塞控制框架ACCF,它可以根据网络状态的变化在现有的拥塞控制机制之间进行自动转换。然后,我们在具有高带宽延迟乘积(BDP)的网络上执行ACCF的简单实现。它可以根据网络状态在基于延迟的基于丢失的拥塞控制方法之间进行切换。基于网络模拟器以及在一天的不同时间段上的实际有线网络上进行了广泛的实验。对于仿真措施,实验结果表明,与其他最新算法相比,ACCF的性能在吞吐量,公平性和TCP友好性方面均得到了显着提高。对于实际的网络测试,实验结果表明,与其他TCP拥塞控制算法的平均吞吐量相比,ACCF的加速比高达225.83%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号