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A novel learning based solution for efficient data transport in heterogeneous wireless networks

机译:一种新颖的基于学习的解决方案,用于异构无线网络中的有效数据传输

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There has been a spectacular growth in the use of wireless networks in recent times and consequently, adapting TCP to the wireless networks is a hot topic of current research. However, most of the existing works proposed for this problem have been designed for specific wireless networks, or they necessitate changes at either the receiver or the intermediate nodes, or at both, because of which their deployment becomes difficult. In this work, we propose a TCP variant which works over both multi-hop ad hoc wireless networks as well as single-hop (last-hop) wireless networks, like Wireless LANs, cellular, and satellite networks. We use a learning based method to dynamically change the congestion window size according to the network conditions. Our protocol does not rely on any explicit feedback from the network and requires only sender-side modifications. Through extensive simulations we show that our protocol achieves the desired goals of performance improvement in goodput, reduction in packet loss, and fairness to the competing flows. To the best of our knowledge, this is the first unified solution for both single-hop and multi-hop wireless networks.
机译:近年来,无线网络的使用有了惊人的增长,因此,使TCP适应无线网络成为当前研究的热点。然而,针对该问题提出的大多数现有工作已经针对特定的无线网络进行了设计,或者它们需要在接收器或中间节点或两者处进行更改,因此,它们的部署变得困难。在这项工作中,我们提出了一个TCP变体,它既可以在多跳自组织无线网络上运行,也可以在单跳(最后一跳)无线网络上工作,例如无线LAN,蜂窝和卫星网络。我们使用一种基于学习的方法来根据网络条件动态更改拥塞窗口的大小。我们的协议不依赖于来自网络的任何显式反馈,仅需要发送方修改。通过广泛的仿真,我们证明了我们的协议达到了预期的性能目标,即提高了吞吐量,减少了数据包丢失以及对竞争流的公平性。据我们所知,这是单跳和多跳无线网络的第一个统一解决方案。

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