TCP with gateway adaptive pacing for multihop wireless networks with Internet connectivity

This paper introduces an effective congestion control pacing scheme for TCP over multihop wireless networks with Internet connectivity. The pacing scheme is implemented at the wireless TCP sender as well as at the Internet gateway, and reacts according to the direction of TCP flows running across the wireless network and the Internet. Moreover, we analyze the causes for the unfairness of oncoming TCP flows and propose a scheme to throttle aggressive wired-to-wireless TCP flows at the Internet gateway to achieve nearly optimal fairness. The proposed scheme, which we denote as TCP with Gateway Adaptive Pacing (TCP-GAP), does not impose any control traffic overhead for achieving fairness among active TCP flows and can be incrementally deployed since it does not require any modifications of TCP in the wired part of the network. In an extensive set of experiments using ns-2 we show that TCP-GAP is highly responsive to varying traffic conditions, provides nearly optimal fairness in all scenarios and achieves up to 42% more goodput for FTP-like traffic as well as up to 70% more goodput for HTTP-like traffic than TCP NewReno. We also investigate the sensitivity of the considered TCP variants to different bandwidths of the wired and wireless links with respect to both aggregate goodput and fairness.     

TCP Yuelu:一种基于有线/无线混合网络端到端的拥塞控制机制

无线链路传输数据的比特率出错导致TCP协议在有线／无线混合网络环境下性能低下,在改进算法TCPReno的基础上,文章提出了一种适用于有线／无线混合网络的拥塞控制机制,该机制包括一种分阶段平滑慢启动机制,改善了突发流量对网络性能的损害,引入网络测量技术获得了往返时间（RTT）、网络带宽、瓶颈链路队列长度等网络状态参数,区分网络拥塞和无线链路比特差错,避免了终端节点对网络状态不了解产生的盲目行为,有效改进了TCP的加性增加乘性减少（AIMD）窗口调节机制,提高了网络性能．同时,在仿真软件NS2中实现了该算法,进行了大量的仿真实验,实验结果表明TCP Yuelu有效降低了网络抖动,提高了网络传输性能,并保持了良好的公平性和对其它TCP流的友好性．     

Improving Throughput of Transmission Control Protocol Using Cross Layer Approach

Most of the internet users connect through wireless networks. Major part of internet traffic is carried by Transmission Control Protocol (TCP). It has some design constraints while operated across wireless networks. TCP is the traditional predominant protocol designed for wired networks. To control congestion in the network, TCP used acknowledgment to delivery of packets by the end host. In wired network, packet loss signals congestion in the network. But rather in wireless networks, loss is mainly because of the wireless characteristics such as fading, signal strength etc. When a packet travels across wired and wireless networks, TCP congestion control theory faces problem during handshake between them. This paper focuses on finding this misinterpretation of the losses using cross layer approach. This paper focuses on increasing bandwidth usage by improving TCP throughput in wireless environments using cross layer approach and hence named the proposed system as CRLTCP. TCP misinterprets wireless loss as congestion loss and unnecessarily reduces congestion window size. Using the signal strength and frame error rate, the type of loss is identified and accordingly the response of TCP is modified. The results show that there is a significant improvement in the throughput of proposed TCP upon which bandwidth usage is increased.     

Learning-TCP: A stochastic approach for efficient update in TCP congestion window in ad hoc wireless networks

In this work, we attempt to improve the performance of TCP over ad hoc wireless networks (AWNs) by using a learning technique from the theory of learning automata. It is well-known that the use of TCP in its present form, for reliable transport over AWNs leads to unnecessary packet losses, thus limiting the achievable throughput. This is mainly due to the aggressive, reactive, and deterministic nature in updating its congestion window. As the AWNs are highly bandwidth constrained, the behavior of TCP leads to high contentions among the packets of the flow, thus causing a high amount of packet loss. This further leads to high power consumption at mobile nodes as the lost packets are recovered via several retransmissions at both TCP and MAC layers. Hence, our proposal, here after called as Learning-TCP, focuses on updating the congestion window in an efficient manner (conservative, proactive, and finer and flexible update in the congestion window) in order to reduce the contentions and congestion, thus improving the performance of TCP in AWNs. The key advantage of Learning-TCP is that, without relying on any network feedback such as explicit congestion and link-failure notifications, it adapts to the changing network conditions and appropriately updates the congestion window by observing the inter-arrival times of TCP acknowledgments. We implemented Learning-TCP in ns-2.28 and Linux kernel 2.6 as well, and evaluated its performance for a wide range of network conditions. In all the studies, we observed that Learning-TCP outperforms TCP-Newreno by showing significant improvement in the goodput and reduction in the packet loss while maintaining higher fairness to the competing flows.     

Multiple TFRC Connections Based Rate Control for Wireless Networks

Rate control is an important issue in video streaming applications for both wired and wireless networks. A widely accepted rate control method in wired networks is equation based rate control , in which the TCP friendly rate is determined as a function of packet loss rate, round trip time and packet size. This approach, also known as TCP friendly rate control (TFRC), assumes that packet loss in wired networks is primarily due to congestion, and as such is not applicable to wireless networks in which the bulk of packet loss is due to error at the physical layer. In this paper, we propose multiple TFRC connections as an end-to-end rate control solution for wireless video streaming. We show that this approach not only avoids modifications to the network infrastructure or network protocol, but also results in full utilization of the wireless channel. NS-2 simulations, actual experiments over 1$times$RTT CDMA wireless data network, and and video streaming simulations using traces from the actual experiments, are carried out to validate, and characterize the performance of our proposed approach.     

Improving TCP fairness and performance with bulk transmission control over lossy wireless channel

The traditional windows-based TCP congestion control mechanism produces throughput bias against flows with longer packet roundtrip times; the flow with a short packet roundtrip time preoccupies the shared network bandwidth to a greater extent than others. Moreover, the blind window reduction that occurs whenever packets are lost decreases the network utilization severely, especially in networks with high packet losses. This paper proposes a sender-based TCP congestion control, called TCP-BT. The scheme estimates the network bandwidth depending on the transmission behavior of applications, and adjusts the congestion window by considering both the estimated network bandwidth and the packet roundtrip time to improve fairness as well as transmission performance. The scheme has been implemented in the Linux platform and compared with various TCP variants in real environments. The experimental results show that the proposed scheme improves transmission performance, especially in networks with congestion and/or high packet loss rates. Experiments in real commercial wireless networks have also been conducted to support the practical use of the proposed mechanism.     

Behavior analysis of TCP Linux variants

The Transmission Control Protocol (TCP) is used by the vast majority of Internet applications. Since its introduction in the 1970s, a lot of variants have been proposed to cope with the different network conditions we can have (e.g., wired networks, wireless networks, satellite links) and nowadays Linux OS includes 13 different TCP variants.The aim of this paper is to offer a comparative analysis of the behavior of the different TCP Linux variants, in terms of throughput, fairness, and friendliness.     

适用于异构网络的改进TCP协议研究

在有线网络中,网络丢包主要是网络拥塞造成的,而传统的TCP协议主要是针对有线网络设计的。对于无线网络,链路错误的随机丢包成为其主要的丢包,传统的TCP已不再适用。为了使TCP适用于有线-无线的异构网络中,提出一种改进的TCP协议(命名为TCP-Ackflag)。此协议通过接收端判断分组数据的相对延迟趋势来判断网络拥塞情况,并在接收端反馈给发送端的ACK包中定义一个拥塞标志位。接收端在接收ACK包中,记录这个拥塞标志位。为了使网络能达到最大吞吐量,发送端只有在发现产生网络丢包现象后再立即对记录的拥塞标志位的值进行检测,通过检测到的拥塞标志位的值来判断网络拥塞情况,最终决定是进入网络拥塞处理过程还是简单地快速重传过程,从而保证了有线-无线异构网络的传输性能。仿真结果表明,此方案对网络拥塞判断准确性和灵敏性都有极大提高,并在此基础上保证了网络传输性能。     

Ad Hoc中的TCP改进方案——Adaptive ADTCP

在分析无线自组网特点及其对TCP性能影响的基础上,提出了一种能够自适应无线自组网状态的TCP改进方案(Adaptive ADTCP）。Adaptive ADTCP在明确辨识网络状态的前提下,首先根据前向路径跳数自适应地调整拥塞窗口增长因子,限制源节点TCP拥塞窗口过分增长,避免造成网络拥塞;同时源节点TCP根据当前拥塞窗口自适应改变发送的分组长度,充分利用网络资源。仿真实验表明,在网络重负载和节点高速移动情况下,Adaptive ADTCP对数据传输的吞吐量有较大提升。     

Achieving high throughput and TCP Reno fairness in delay-based TCP over large networks

The transport control protocol (TCP) has been widely used in wired and wireless Internet applications such as FTP, email and http. Numerous congestion avoidance algorithms have been proposed to improve the performance of TCP in various scenarios, especially for high speed and wireless networks. Although different algorithms may achieve different performance improvements under different network conditions, designing a congestion algorithm that can perform well across a wide spectrum of network conditions remains a great challenge. Delay-based TCP has a potential to overcome above challenges. However, the unfairness problem of delay-based TCP with TCP Reno blocks widely the deployment of delay-based TCP over wide area networks. In this paper, we proposed a novel delay-based congestion control algorithm, named FAST-FIT, which could perform gracefully in both ultra high speed networks and wide area networks, as well as keep graceful fairness with widely deployed TCP Reno hosts. FAST-FIT uses queuing delay as a primary input for controlling TCP congestion window. Packet loss is used as a secondary signal to adaptively adjust parameters of primary control process. Theoretical analysis and experimental results show that the performance of the algorithm is significantly improved as compared to other state-of-the-art algorithms, while maintaining good fairness.     

V2G网络中基于带宽自适应的拥塞控制协议优化

V2G网络下PLC链路带宽受限、高误码率等特点导致现有的TCP NewReno拥塞控制机制缺乏对丢包类型的有效判断,将链路上由噪声干扰的随机错误丢包与网络拥塞丢包统一当做拥塞事件处理,从而造成不必要的拥塞避免,导致了低吞吐量问题.根据此问题,提出了一种基于带宽自适应的拥塞控制算法.该算法通过分组预测拥塞等级感知网络状态,由此估计可用带宽来判断丢包类型,实现了拥塞窗口自适应调节.仿真结果表明该算法在拥塞窗口的增长、吞吐量、公平性、收敛性和友好性等方面都优于现有算法,V2 G网络的吞吐量得到明显提升.     

LEO卫星网中自适应的TCP方法

针对LEO卫星网中不同连接时延差别大、TCP性能降低、公平性较差等问题,提出基于路径中卫星数调节TCP初始窗口和窗口增大速度以改善较长时延连接性能的方法。推导出新的拥塞控制窗口增长公式,区别对待不同时延的连接,具有自适应能力。仿真结果表明,该方法能有效提高长时延条件下TCP的性能,在不同时延的连接间公平性指数接近于1,适用于多种版本TCP在LEO卫星网中的改进。     

一种基于带宽估计的无线网拥塞控制机制

针对无线网提出了一种基于带宽估计的拥塞控制机制。该机制利用TCP确认帧携带的数据包到达时间来估算包到达速率，从而得到带宽的估计值。在此基础上用带宽的估计值更新拥塞窗口，避免在发生链路错误时启动拥塞控制机制，由此提高了TCP在无线网上的性能。实验结果表明，算法能减少链路差错对TCP性能带来的影响，提高了TcP在无线网上的吞吐率。     

一种Ad Hoc网络端到端的TCP拥塞控制改进方案

传统的TCP协议是为有线网络而设计的,它假定数据包的丢失是由网络拥塞引起的,然而在Ad Hoc网络中,除拥塞丢包外,其它非拥塞因素也会引起数据包的丢失。分析Ad Hoc网络影响TCP性能的主要因素,在原有拥塞控制方案MMJI的基础上,提出了一种端到端的TCP拥塞控制改进方案（Imp MMJI）。该方案能根据前向路径跳数自适应调整拥塞窗口的大小,防止拥塞窗口过快增长,当发生路由改变或链路中断时,重新计算拥塞窗口cwnd和ssthresh的值,以确保路由重建前后TCP连接负载率的一致性;并在ACK应答包的TCP首部增加了状态标志位,结合多个度量参数联合判断网络状态,提高网络状态识别的准确性,使发送端实时采取相应的措施。仿真结果表明,该方案能使网络吞吐量得到明显的提高,改善了TCP的性能。     

加密环境中的无线TCP性能优化

TCP是一种广泛使用的可靠传输协议,它的设计基于拥塞是引起丢包主要原因的假设。但在无线网络中,丢包通常是传输差错的缘故,这导致了TCP传输性能的急剧下降。现有不少无线TCP传输性能优化方法要求中间节点能够获得TCP连接信息,因此不适用于数据流被加密的情况。文中提出的丢包识别机制可应用于加密环境,它通过TCP发送端判断丢包原因并采取相应措施来提高传输速率,仿真结果证明该方法是有效的、鲁棒的,在局域网和广域网环境中都能明显提高TCP端到端传输性能。     

Can high-speed networks survive with DropTail queues management?

It has been observed that TCP connections that go through multiple congested links (MCL) have a smaller transmission rate than the other connections. Such TCP behavior is a result of two components (i) the cumulative packet losses that a flow experiences at each router along its path; (ii) the longer round trip times (RTTs) suffered by such flows due to non-negligible queueing delays at congested routers. This double “bias” against connections with MCLs has been shown to approximate the so-called minimum potential delay fairness principle in the current Internet. Despite the recent proliferation of new congestion control proposals for TCP in high-speed networks, it is still unclear what kind of fairness principle could be achieved with such newly proposed congestion control protocols in high-speed networks with large-delays. Studies already show that some high-speed TCP variants may cause surprisingly severe RTT unfairness in high-speed networks with DropTail routers.This paper studies the problem of unfairness in high-speed networks with some well-known high-speed TCP variants in presence of multiple congested links and highlights the severity of such unfairness when DropTail queue management is adopted.Through a simple synchronized loss model analysis, we show how synchronized losses with DropTail in high-speed networks could lead to severe RTT unfairness and drop probability (DP) unfairness; while random marking AQM schemes, which break the packet loss synchrony mitigate such unfairness dramatically by ensuring that the packet loss probability of a flow is the sum of the loss probabilities on the congested routers it crosses.Extensive simulations are carried out and the results support our findings.     

一种丢包区分方法及其在Linux下的实现

针对传统拥塞控制机制在无线链路丢包的情况下出现的盲目降低拥塞窗口、TCP吞吐量下降的问题,研究无线/有线混合环境下基于该机制的一种丢包区分方法——WECN,在Linux操作系统下进行实现。搭建混合网络实验床仿真WECN与TCP Reno, TCP Westwood 2种协议相结合的网络模型。测试结果表明,WECN能扩展到已有的TCP协议中,提高含无线链路网络中TCP的吞吐量。     

基于GEO卫星链路丢包区分的TCP Westwood改进算法

在分析TCP Westwood (TCPW)算法优缺点的基础上,针对其应用于同步轨道(GEO)卫星链路时存在的不足,结合Vegas、Veno及LogWestwood+等改进算法的优势,基于预测的下一时刻的网络带宽,把窗口调整与带宽利用情况相结合,提出了一种新的适合于GEO卫星链路的基于丢包区分的TCP Westwood改进算法。改进算法将每个阶段的窗口调整与带宽估计、网络状态紧密联系起来,结合网络状态和带宽估计判断拥塞窗口的合理性,动态地调整拥塞窗口,使拥塞即将发生时,窗口能及时下降到适宜的水平,尽量避免由于拥塞而导致的分组丢失。仿真结果表明,改进算法提高了TCP westwood在GEO卫星链路中应用时的性能,具有较好的吞吐量、公平性、友好性和较低的丢包率。     

Adaptive load balancing algorithm for multiple homing mobile nodes

In places where mobile users can access multiple wireless networks simultaneously, a multipath scheduling algorithm can benefit the performance of wireless networks and improve the experience of mobile users. However, existing literature shows that it may not be the case, especially for TCP flows. According to early investigations, there are mainly two reasons that result in bad performance of TCP flows in wireless networks. One is the occurrence of out-of-order packets due to different delays in multiple paths. The other is the packet loss which is resulted from the limited bandwidth of wireless networks. To better exploit multipath scheduling for TCP flows, this paper presents a new scheduling algorithm named Adaptive Load Balancing Algorithm (ALBAM) to split traffic across multiple wireless links within the ISP infrastructure. Targeting at solving the two adverse impacts on TCP flows, ALBAM develops two techniques. Firstly, ALBAM takes advantage of the bursty nature of TCP flows and performs scheduling at the flowlet granularity where the packet interval is large enough to compensate for the different path delays. Secondly, ALBAM develops a Packet Number Estimation Algorithm (PNEA) to predict the buffer usage in each path. With PNEA, ALBAM can prevent buffer overflow and schedule the TCP flow to a less congested path before it suffers packet loss. Simulations show that ALBAM can provide better performance to TCP connections than its other counterparts.     

APS-FeW: Improving TCP throughput over multihop adhoc networks

TCP is a reliable transport protocol tuned to perform well over traditional wired networks. Although it performs well for wired networks, TCP’s implicit assumption that any packet loss is due to congestion is not valid any longer in mobile ad hoc networks. It is observed that TCP induces the over-action of routing protocol and reduces the performance of the connection. Fraction window increment (FeW) scheme for TCP improves the connection performance by limiting TCP’s aggressiveness. But to some extent, this limitation is too strict in that it eliminates the possibility to deliver more bytes under the same congestion window. To solve this problem, we propose an adaptive packet size (APS) scheme to work on top of FeW for TCP. The proposed scheme utilizes the advantages of both legacy TCP and FeW to achieve high performance over multihop 802.11 networks. Extensive simulation results demonstrate that APS over FeW outperforms FeW alone by 10–25% according to different scenarios, e.g., chain-topology, grid-topology, and random-topology with mobility.