Enhancing MPTCP performance in wireless networks with PRS-MPTCP

Multipath Transmission Control Protocol (MPTCP) is in a rapid development process. MPTCP allows a network node to utilize multiple network interfaces and IP paths at the same time. It can take full advantage of network resources and provide reliable transmission, which brings advantages to users in terms of performance and reliability. In order to study the performance of MPTCP under high load, this paper uses Mininet to create an SDN environment and compare the performance differences between MPTCP and TCP under high load, and simulates a common Web application network architecture. The performance of MPTCP under this architecture is tested and analyzed. The test results show that MPTCP performs better than traditional TCP under high load. Besides, its performance can be optimized furtherly by adjusting related parameters.

A popular transport layer protocol that makes extensive use of multi-path communication technology is called Multi-Path Transmission Control Protocol (MPTCP). Making use of the end-host’s multi-interface capabilities is MPTCP’s primary goal. However, the protocol’s main weakness is lower channel usage suffers from a sharp decline in throughput due to its sudden congestion window (cwnd) growth policy. Furthermore, the performance of MPTCP is significantly reduced when there are many possible channels for transmission because different wireless path parameters such as bandwidth, loss rate (due to congestion or unreliability of the wireless channel), and delay necessitate higher re-ordering at the receiver end. As a result, it causes a significant increase in buffer-blocking and needless retransmissions. Nonetheless, a few strategies that efficiently schedule and distribute the load over accessible, qualifying channels have been proposed. However, our proposed policy takes all these parameters into consideration and the performance has been improved significantly can be seen be the graphs presented in the later section of the paper.

Space-ground integrated networks (SGINs) have been recently regarded as a promising way to provide resilient, dependable as well as efficient data transmission in the high-speed railway (HSR) scenario. Applying multipath transmission control protocol (MPTCP) to SGIN can realize data transmission simultaneously via terrestrial and satellite networks. However, since the existing congestion control (CC) mechanisms of MPTCP fail to distinguish between adverse influences (such as packet loss and/or round-trip time increase) caused by congestion and those caused by handovers, it suffers severe performance degradation in the HSR scenario where handover frequently occurs. In this article, we first present the SGIN oriented HSR (SGIN-HSR) with MPTCP. Then leveraging cross-layer information (i.e., reference signal received power), we design a novel cross-layer aided MPTCP CC mechanism targeted at SGIN-HSR based on deep reinforcement learning, which is referred to as HSR-CC, to alleviate performance degradation problems induced by handover. The experimental results show that HSR-CC significantly enhances the goodput and outperforms state-of-the-art MPTCP CC algorithms in SGIN-HSR environments where handover frequently occurs.

Multipath TCP (MPTCP) is a backward compatible extension of Transmission Control Protocol (TCP) designed to let an application send data over several TCP connections, usually called subflows. MPTCP presents several opportunities over legacy TCP, especially when these subflows follow disjoint paths: for instance bandwidth aggregation or seamless mobility across networks. While MPTCP is built as an extension of TCP, the scope of the modifications qualifies it almost as a new protocol. This means traditional TCP tools are not enough to analyze MPTCP performance. We thus develop and present an open source application able to analyze MPTCP specific metrics such as the aggregated goodput or inter-subflow retransmissions.

With increasing deployment of Multipath TCP (MPTCP) in multihoming and data enter scenarios, there is a need to understand how its performance is affected in practice-both by traditional factors such as RTT measurements, and by new multipath-specific considerations such as sub flow selection. We carried out an initial but comprehensive study using an actual MPTCP implementation in an emulated network environment, to explore the impact of different factors on MPTCP throughput. We find that path selection and packet scheduling have a large effect on performance, and that merely trusting the congestion control mechanism to do the right thing is not enough. Moreover, we provide evidence that throughput can be improved by slight modifications to the send buffers and path selection components of the implementation. Important challenges in network design remain, if only to ensure that multiple suitable paths exist in a network.

Today's laptops and mobile terminals are equipped with several network interfaces belonging to different access technologies. Users can benefit from multi-homing to access network services anywhere, at any time and from any network. Multipath TCP (MPTCP) is a modified version of Transmission Control Protocol (TCP) which allows a TCP connection to simultaneously send data over multiple paths. One of the objectives of MPTCP is to improve the throughput of TCP connection. A MPTCP connection over multiple paths should achieve a no worse throughput than a single TCP connection over the best constituent path. In this paper, we evaluate the performance of MPTCP in terms of throughput optimization and load sharing. The measurements show that the context of heterogeneous networks (Ethernet, Wifi and 3G) has a great impact on the MPTCP performances and reveal the need of an intelligent algorithm for interface selection in MPTCP.

Modern computing devices such as smartphones and personal computers provide multiple network interfaces such as WiFi and 3G/LTE cellular network. Multipath TCP (MPTCP) is a commonly proposed method of aggregating the bandwidth of these interfaces. However, how MPTCP affects the quality of experience of existing services, especially to variances in bandwidth and latency among the individual paths over the wireless networks is not well-known. In this work, we explore the quality of service (QoS) and quality of experience (QoE) of adaptive video streaming using MPTCP over wireless network given its vast popularity and significant bandwidth demand. Unlike prior works, we conduct systematic measurements over three mobile network operators, AT&T, Verizon Wireless (VzW), and T-Mobile, along with WiFi. Based on extensive measurements, we show that MPTCP can improve the QoS and QoE of video streaming only if the network interfaces have the roughly similar bandwidth and latency. Our studies also show that MPTCP can perform worse than TCP in case of extreme differences between the network interfaces.

Mobile devices are able to leverage diverse heterogeneous network paths by Multi-Path Transmission Control Protocol (MPTCP); nevertheless, boosting MPTCP throughput in wireless networks is a real bear. Not only the best path(s) should be selected, but also the optimal congestion control mechanism should be chosen. We investigate the impact of different paths and congestion control for different signal quality states. Consequently, we present the novel MPTCP algorithm augmenting the end user throughput by understating the best policy in different situations by Q-learning. The Results reveal a tremendous effect of switching between the different interfaces and changing the congestion control mechanism on throughput and delay. By and large, the proposed framework achieves 10% more throughput compared to base MPTCP.

The upgrade of network devices to be equipped with multiple network interfaces makes it possible to improve network throughput performance through multipath transmission protocols, especially multipath TCP (MPTCP). However, so far the mostly used MPTCP protocols have a common limitation, namely the rigid and conservative method. They have been designed with little consideration of the fact that real networks are dynamic and the network status changes frequently, thus leading to the poor performance of current MPTCP in many realistic scenarios. In this paper, we propose a lightweight multipath congestion control algorithm based on online learning, named MP-OL. MP-OL models congestion control as a multi-armed bandit problem, and adjusts the sending rate of each subflow flexibly and adaptively through online learning. Therefore, MP-OL possesses the capability of suiting various network scenarios, and can achieve fairness and high performance in dynamic network environment. It can also flexibly switch between online learning and traditional method, which reduces the computational complexity while ensuring the learning efficiency, thus making MP-OL easy to deploy and use. As the experimental results demonstrated, compared with the leading MPTCP variants, MP-OL achieves significant improvements in fairness and link utilization, and shows better resilience to non-congestion loss and better adaptability to unstable network conditions. In real networks, MP-OL also obtains better throughput performance.

Nearly 50% of the energy overhead in today's datacenters comes from host-to-host data transfers, which largely depend on the transport layer performance. Multipath TCP (MPTCP) has recently been suggested as a promising transport protocol to improve datacenter network throughput, yet it also increases the host CPU power consumption. It remains unclear whether datacenters can indeed benefit from using MPTCP from the perspective of energy efficiency. By analyzing the performance of MPTCP, we show that (1) despite consuming higher host CPU power than TCP, MPTCP can largely reduce the long flow completion time and thus save the aggregated energy; (2) link-sharing subflows in MPTCP not only has negative impact on both throughput-sensitive long flows and latency-sensitive short flows, but also noticeably increases the host CPU power, especially for short flows. We present MPTCP-D, an energy-efficient variant of multipath TCP for datacenters. MPTCP-D incorporates a novel congestion control algorithm that can provide energy efficiency by minimizing the flow completion time, and an extra subflow elimination mechanism that can preclude link-sharing subflows from increasing the host CPU power. We implement MPTCP-D in the Linux kernel and study its performance by experiments on Amazon EC2. Our results show that, without degrading the performance of the long flow throughput and short flow completion time, MPTCP-D reduces the long flow energy consumption by up to 72% compared to DCTCP for data transfers, and reduces the short flow power consumption by up to 46% compared to MPTCP with linksharing subflows.

Multipath TCP (MPTCP) is a promising technique for boosting application throughput while using well-known and versatile network socket interfaces. Recently, many interesting applications of MPTCP in various environments such as wireless networks and data centers have been proposed, but little work has been done to investigate the impact of this protocol on conventional network devices. For example, MPTCP throughput advantage can be better achieved if all MPTCP subflows are routed on disjoint paths, but this is currently not feasible since routers are not designed to recognize the membership of MPTCP subflows. In this paper, we take a first step to address this issue by proposing SAMPO, an online algorithm to detect and associate MPTCP subflows in network. The main challenge is that sampling techniques and network dynamics may cause a network device to only obtain partial flow records. SAMPO takes advantage of both protocol information and statistical characteristics of MPTCP data sequence number to overcome the challenge in network. Through analysis and experimentation, we show that SAMPO is able to detect and associate MPTCP subflows with high accuracy even when a small portion of the entire flow records are available.

Multipath TCP (MPTCP) is the most significant extension of TCP that enables transmission via multiple paths concurrently to improve the resource usage and throughput of long flows. However, due to the concurrent multiple transfer (CMT) in short flow trans-mission, the congestion window (cwnd) of each MPTCP subflow is too small and it may lead to timeout when a single lost packet cannot be recovered through fast retransmission. As a result, MPTCP has even worse performance for short flows compared to regular TCP. In this paper, we take the first step to analyze the main reason why MPTCP has the diminished performance for short flows, and then we propose MPTCP-SF, which dynamically adjusts the number of subflows for each flow . In particular, MPTCP-SF firstly analyzes the distribution characteristics of the web objects to extract two thresholds to be used for classifying each flow. After eceiving each new ACK, MPTCP-SF periodically counts the data being sent based on per-flow and uses the threshold to classify the we blows. Finally, MPTCP-SF dynamically switches path scheduling model for different classification flows. We conduct extensive experiments in NS3 to evaluate its e fficiency. Our evaluation proves that MPTCP-SF decreases the completion time of short flows by over 42.64% com-pared to MPTCP, and the throughput achieved by MPTCP-SF in transmitting long flows is about 11.11% higher than that of MPTCP in a WLAN/LTE wireless network. The results successfully validate the improved performance of MPTCP-SF.

Multipath TCP (MPTCP) is a major extension of TCP that aims to offer higher aggregate bandwidth and robustness by pooling multiple paths within one transport connection. One of the current weaknesses of the protocol is the Delayed ACK scheme inherited from TCP. The Delayed ACK is an option of TCP that allows the receiver to delay sending an ACK for every other packet within a window given by the Delayed ACK timer. At the sender, the RTO should be no less than the Minimum RTO to avoid spurious timeouts. This strategy can lead to significant performance degradation in the presence of timeouts, especially in high speed networks, where RTT is usually one- or two-order of magnitude smaller than the Minimum RTO. When a subflow occurs a timeout, the receiver has to buffer data from all the subflows until the missing packet is received. The data may overrun the receive buffer to cause flow control at the sender, which seriously impacts the overall performance. In order to avoid MPTCP performance degradation, we propose a new Delayed ACK aiming to remove the Minimum RTO constraint at the sender while to reserve the Delayed ACK function at the receiver. Our solution requires only minor modification to the legacy Delayed ACK scheme and it introduces negligible computational overhead and no extra traffic overhead. We use a NS-3 network simulator to evaluate the performance of our new Delayed ACK in three typical network environments. The results indicate that MPTCP using new Delayed ACK scheme requires much smaller aggregate buffer than MPTCP using the legacy Delayed ACK scheme, especially in high speed networks where the buffer requirement reduces one- or two-order of magnitude.

A significant enhancement in recent communication systems is Satellite Communications. The performance improvement of the transmission control protocol (TCP) in satellite communications has been an active research area. Multipath TCP (MPTCP) ensures a robust solution than the regular TCP. However, the performance degradation in satellite networks due to the link asymmetry, high loss and high latency cannot distinguish the packet losses caused by network congestions from the losses properly. In this paper, a round-trip time detection-based algorithm is proposed using available bandwidth estimation (ABE) to mitigate the issue of blind decreasing of congestion window upon detecting the packet loss over lossy satellite networks. Experiments are done using the NS-2 network simulator to compare the various congestion control algorithms of both TCP and MPTCP over satellite networks. Simulations results from the experiments show that our proposed algorithm outperforms the existing algorithms which are mentioned in this article.

Packet loss and error propagation induced by it are significant causes of visual impairments in video applications. Most of the existing video quality assessment models are developed at frame or sequence level, which can not accurately describe the impact of packet loss on the local regions in one frame. In this paper, we propose an error sensitivity model to evaluate the impact of a single packet loss. We also make full use of the spatio-temporal correlation of the video and analyze a set of features that directly impact the perceptual quality of videos, based on the specific situation of video packet loss. With the aid of the support vector regression (SVR), these features are used to predict the error sensitivity of the local region. The proposed model is tested on six video sequences. Experimental results show that the proposed model predicts sensitivity of videos to different packet loss cases with certain reasonable accuracy, and provides good generalization ability, which turns out outperform the state-of-art image and video quality assessment methods.