LISA: A linked slow-start algorithm for MPTCP

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.

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.

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.

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.

Recent data centers provide dense inter-connectivity between each pair of servers through multiple paths. These data centers offer high aggregate bandwidth and robustness by using multiple paths simultaneously. Multipath TCP (MPTCP) protocol is developed for improving throughput, fairly sharing network link capacity and providing robustness during path failure by utilizing multiple paths over multi-homed data center networks. Running MPTCP protocol for latency-sensitive rack-local short flows with many-to-one communication pattern at the access layer of multi-homed data center networks creates MPTCP incast problem. In this paper, Balanced Multipath TCP (BMPTCP) protocol is proposed to mitigate MPTCP incast problem in multi-homed data center networks. BMPTCP is a window-based congestion control protocol that prevents constant growth of each worker’s subflow congestion window size. BMPTCP computes identical congestion window size for all concurrent subflows by considering bottleneck Top of Rack (ToR) switch buffer size and increasing count of concurrently transmitting workers. This helps BMPTCP to avoid timeout events due to full window loss at ToR switch. Based on current congestion situation at ToR switches, BMPTCP adjust transmission rates of each worker’s subflow so that total amount of data transmitted by all concurrent subflows does not overflow bottleneck ToR switch buffer. Simulation results show that BMPTCP effectively alleviates MPTCP incast. It improves goodput, reduces flow completion time as compared to existing MPTCP and EW-MPTCP protocols.

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.

Satellite systems might become an important supplement to 5G systems. In addition, compared with regular TCP, multipath TCP (MPTCP) provides a robust solution. However, due to the high latency and high loss of satellite networks, most of the existing multipath TCP congestion control schemes do not perform well. Therefore, we proposed a bandwidth and round-trip time detection-based congestion control (BWRD) for multipath TCP over highly lossy satellite networks. Simulations are running to evaluate the proposed BWRD algorithm. It is shown that compared to previous solutions, our strategy significantly improves throughput performance and guarantees the fairness among the various sub-flows.

Multipath Transmission Control Protocol (MPTCP) enables multi-homed devices to establish multiple simultaneous routes for data transmission. Congestion Control (CC) is a fundamental mechanism for implementing and designing MPTCP. The Internet of Things (IoT) networks generate a massive volume of heterogeneous traffic with high dimensional states and diverse QoS characteristics. The existing MPTCP CC algorithms are unable to perform efficiently under highly mobile and dynamic IoT environments. We propose a novel model-free SDN-based adaptive actor-critic deep reinforcement learning framework based on a fuzzy normalized neural network to address the issue of CC for MPTCP in the IoT networks. In the proposed method, an agent can learn efficiently and better approximate the state-action value function of the actor and the action function of the critic to adjust the sub-flows congestion windows size adaptively according to the dynamic condition of a network. Simulation results show that the proposed scheme outperforms the state of the art schemes in terms of the goodput under highly-dynamic IoT environments.

Congestion is a major factor which affects the data center network traffic. Major applications of data center producing huge data traffic are social networks, online shopping portals, online banking portals, mobile application data, weather forecasting applications, Internet of Things applications and so on. Handling such large amount of data is a difficult task for data center architectures and mechanisms and always lead to congestion. The congestion control mechanisms already proposed in existing research works for Software Defined Data Centers lack behind in terms of scalability and throughput due to increase in data center traffic and centralized controller environment. So, in this paper, we are proposing a Simple Congestion Avoidance mechanism for Multipath Transmission Control Protocol traffic using Random Early Detection Algorithm to overcome the limitation of huge packet loss for a specific flow and detection of congested links in the early stage. In our proposed work, path generation among the particular source and destination has been carried out as Multipath Transmission Control Protocol traffic which can prevent congestion state due to the generation of sub flows between two hosts. Then, we bring up Random Early Detection mechanism as a congestion avoidance strategy to minimize overloaded links, link delay and to enhance throughput during packet transmission. This implementation is carried out in the network simulator, Mininet with OpenDaylight controller setup which runs on the top of Jellyfish data center topology. We finally compare the performance of proposed work with an existing congestion avoidance mechanism and show that our implementation offers better throughput by considering the link load, capacity for different node ranges.

TCP was originally designed for single session, thus could not utilize resources of multiple paths. MPTCP (Multipath TCP) provides enhanced performance and reliability by using multiple paths simultaneously at the Transport layer. But, LIA based congestion control of basic MPTCP does not show good performance when characteristics of two path are asymmetrical in the aspects of bandwidth in high-speed networks. In this paper, we suggest new MPTCP control scheme by applying TCP CUBIC on the high-speed path and modified LIA on the other low-speed data path. Our proposed scheme can enhance performance of high-speed asymmetric path more than 4 times compared to the basic MPTCP protocol.

A path characteristics based adaptive subflow switching algorithm for dynamic heterogeneous MPTCP network

The number of mobile terminals that have both a cellular interface and a Wi-Fi interface has been growing in the recent years. Meanwhile, Multipath TCP (MPTCP) that enables the simultaneous use of multiple paths with multiple TCP flows while showing just one regular TCP connection with the application has been standardized by the IETF and has drawn more attention recently. One feature of MPTCP is that it can be realized only by operating system layers supporting multipath communication without any modifications of the application. However, it might be difficult to install MPTCP in all server operating systems. In this paper, we propose a method for applying a proxy that forwards TCP communication from a server to MPTCP communication on a mobile core network, and show the results of evaluation with the existing equipment.

MP-TCP (MultiPath-Transmission Control Protocol) was designed to use multiple interfaces in hosts; it uses several subflows (a set of regular TCP connections) to increase the performance compared to TCP. However, when a host has only one network interface but several subflows are created, they follow the same path to their destination generating bottlenecks and MP-TCP advantages are lost. This paper presents a solution to the shared-bottleneck problem using SDN (Software Defined Networking). A plugin for OpenDayLight is developed for implementing Dijkstra's Algorithm to find paths and assign them to new subflows avoiding bottlenecks. The solution supports concurrent MP-TCP connections. Results of tests obtained using the implemented plugin in several topologies are presented.

Multipath TCP (MPTCP) is a promising TCP extension that exploits different Internet paths between a pair of hosts to obtain high aggregate throughput, while it also brings the concern of energy consumption. There has been a lively interest in the design of energy-efficient MPTCP. The research community, however, lacks a comprehensive understanding of which components in an MPTCP congestion control algorithm play the fundamental role in energy efficiency, how various algorithms compare against each other from energy-consuming perspective, or whether there exist potentially better solutions for energy saving. This paper takes the first step towards answering these questions. Through realworld MPTCP Linux kernel experiments, we show that the energy consumption is related to three major aspects: average throughput, path delay and different network scenarios. In order to bridge congestion control to the three aspects, we analyze the existing algorithms and capture the essential parameters of multipath congestion control model related to energy efficiency. Then we propose a window increase factor to shift traffic to low-delay energy-efficient paths. To further extend this design, we apply an energy-aware compensative parameter to fit the general hierarchical Internet topology. Our evaluation indicates that the enhanced congestion control module can successfully improve MPTCP energy efficiency without affecting its transmission 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.