Multipath TCP Research Articles

Implementation Based Approach to analyze MPLS and Segment Routing Traffic by Using ODL SDN Controller

Network infrastructure in the data center is getting more complicated due to heavy network traffic, by increasing a network load leads high storage consumption and high deployment cost. We have proposed an effective traffic management mechanism by combining Segment Routing and Multipath Transmission Control Protocol TCP in a logically centralized controller environment. Segment Routing and Multipath TCP is used to define a logically centralized and physically distribution for Software Defined Network SDN. Segment Routing SR technology is used for simplifying Multi-protocol Label Switching MPLS and software- defined network SDN networks. Segment Routing makes it easy to assign a dynamic traffic according to customer’s requirements through the high-level application. This work presents a comprehensive comparison between MPLS and Segment Routing Traffic Engineering, both technologies are implemented in an SDN network environment, based on GNS3 network Emulator as data network Layer, Open-Daylight as SDN Controller, and Python scripts for sending Segment IDs as a part of network Orchestrator in Application Layer.

Model and simulations of multipath bridge routing for inter-swarm UAV communications in EMANE/CORE

ABSTRACT The unmanned aerial vehicle (UAV) network is a special type of mobile ad hoc network (MANET). 1 There are two types of UAV swarm communications: Communications within a swarm (i.e. intra-swarm) and communication between different swarms (i.e. inter-swarm). This paper proposes the concept of bridge routing to establish the route(s) for efficient inter-swarm communications. The bridge routing scheme is a progressive process with two functions: UAV formation control and data transmissions. Based on the bridge routing topology, we have implemented the multipath user datagram protocol (MP-UDP), as a sub-layer between the transport and application layers. Compared with the multipath transmission control protocol (MP-TCP), MP-UDP is more suitable to the dynamic network topologies, since it does not use the high-overhead sliding window control. We have used the emulator tools, the Extendable Mobile Ad -hoc Network Emulator (EMANE) and Common Open Research Emulator (CORE) to implement and study the QoS performance of MP-UDP and bridge routing in UAV swarm networks. Our results demonstrate the improved throughput performance for inter-swarm communications. Approved for Public Release; distribution unlimited 88ABW-2020-2122 on 13 July 2020. Other requests shall be referred to AFRL/RIT 525 Brooks Rd Rome, NY 13,441

Can Multipath TCP Be Robust to Cyber Attacks? A Measuring Study of MPTCP with Active Queue Management Algorithms

With the development of social networks, more and more mobile social network devices have multiple interfaces. Multipath TCP (MPTCP), as an emerging transmission protocol, can fit multiple link bandwidths to improve data transmission performance and improve user experience quality. At the same time, due to the large-scale deployment and application of emerging technologies such as the Internet of Things and cloud computing, cyber attacks against MPTCP have gradually increased. More and more network security research studies point out that low-rate distributed denial of service (LDDoS) attacks are relatively popular and difficult to detect and are recognized as one of the most severe threats to network services. This article introduces six classic queue management algorithms: DropTail, RED, FRED, REM, BLUE, and FQ. In a multihomed network environment, we perform the performance evaluation of MPTCP under LDDoS attacks in terms of throughput, delay, and packet loss rate when using the six algorithms, respectively, by simulations. The results show that in an MPTCP-enabled multihomed network, different queue management algorithms have different throughput, delay, and packet loss rate performance when subjected to LDDoS attacks. Considering these three performance indicators comprehensively, the FRED algorithm has better performance. By adopting an effective active queue management (AQM) algorithm, the MPTCP transmission system can enhance its robustness capability, thus improving transmission performance. We suggest that when designing and improving the queue management algorithm, the antiattack performance of the algorithm should be considered: (1) it can adjust the traffic speed by optimizing the congestion control mechanism; (2) the fairness of different types of data streams sharing bandwidth is taken into consideration; and (3) it has the ability to adjust the parameters of the queue management algorithm in a timely and accurate manner.

A Low-Latency MPTCP Scheduler for Live Video Streaming in Mobile Networks

It is a known issue that low-latency communication is hard to achieve when using multiple network interfaces with asymmetric capacity and delay (e.g., LTE and WLAN) simultaneously. A main underlying cause of this issue is that the packets with lower sequence number are stalled on a high-latency path, thus the early arriving packets with higher sequence number become “out-of-order (OFO)” packets. These OFO packets may excessively consume receiver’s buffer, causing long reordering delay and unnecessary packet retransmission. In this paper, we present a novel design of packet scheduling for Multipath TCP (MPTCP), called OverLapped Scheduler (OLS), able to tackle the OFO-packet problem more effectively. OLS can guarantee sufficient throughput on demand of upper layer applications, and utilizes the remaining bandwidth to reduce OFO-packets. To do so, OLS schedules packets according to their arrival time and sends a controlled number of redundant packets to avoid the impact of inaccurate arrival-time estimations due to network jitter. We implement OLS in a Linux kernel, and the experiments show that in asymmetric networks with or without jitter, OLS can effectively reduce OFO-packets and transmission latency while maintaining a sufficient throughput, which makes it fully capable to meet the requirements of applications such as live video streaming.

Reinforcement Learning-Based Mobile AR/VR Multipath Transmission With Streaming Power Spectrum Density Analysis

Multi-path transmission control protocol (MPTCP) is an extension of TCP that enables the concurrent transmission of information through different network interfaces (e.g., Cellular, Wi-Fi, 802.11p, and so on) available at terminal side. It is well known that MPTCP can provide significant advantages in bandwidth aggregation and transmission stability. Unfortunately, path diversity can limit bandwidth aggregation efficiency and incur higher delays. These issues become critical when in presence of emerging mobile AR and VR applications, which are bandwidth hungry, time-sensitive and exhibit abrupt variations of the bitrate. To address these issues, we propose the <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</u> einforcement <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</u> earning-based mobile AR/VR multipath transmission with streaming <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</u> ower <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</u> pectrum <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</u> ensity analysis (RL-PSD). RL-PSD analyses the Power Spectrum Density (PSD) of the AR/VR input stream to extract its features. Then, both the input stream and network features are considered to model the MPTCP congestion control as an reinforcement learning process. Finally, a two-stage reinforcement algorithm is proposed to optimize transmission performance. RL-PSD has been tested in both single-terminal and multi-terminal scenarios: results show that it outperforms the other advanced solutions conceived to support the multipath transmission of AR/VR streams.

Evaluation of MPTCP Schedulers in Diverse Scenarios

Multipath Transmission Control Protocol (MPTCP) is an extension of TCP meant for multihomed devices, which uses all the available interfaces for a single connection. MPTCP was evolved for Bandwidth aggregation and re silence to network failure. The wireless networks of multihomed devices are of different characteristics, when used together decreases Quality of Service (QoS). MPTCP schedulers tried to fill this gap with different approaches. In this paper we tried to study these schedulers in different network scenarios and came with the findings that to achieve good throughput and decrease download time, only fast paths are preferred.

A Brief Review of Multipath TCP for Vehicular Networks.

Multipath TCP (MPTCP) is one of the most important extensions to TCP that enables the use of multiple paths in data transmissions for a TCP connection. In MPTCP, the end hosts transmit data across a number of TCP subflows simultaneously on one connection. MPTCP can sufficiently utilize the bandwidth resources to improve the transmission efficiency while providing TCP fairness to other TCP connections. Meanwhile, it also offers resilience due to multipath data transfers. MPTCP attracts tremendous attention from the academic and industry field due to the explosive data growth in recent times and limited network bandwidth for each single available communication interface. The vehicular Internet-of-Things systems, such as cooperative autonomous driving, require reliable high speed data transmission and robustness. MPTCP could be a promising approach to solve these challenges. In this paper, we first conduct a brief survey of existing MPTCP studies and give a brief overview to multipath routing. Then we discuss the significance technical challenges in applying MPTCP for vehicular networks and point out future research directions.

IoT Traffic Offloading with MultiPath TCP

The concept of a fully connected world in the fifth generation technology envisions the massive rollout of small and constrained Internet of Things (IoT) devices. In such IoT environments, machine-to-machine (M2M) communications is key for allowing these devices (e.g., sensors, actuators, smart meters/monitors) to collect data toward a remote server. We address this particular scenario by building and evaluating an IoT multi-access reference architecture, with a multipath TCP (MPTCP) gateway connected to multiple cellular networks to offload M2M data traffic. Experimental results from CoAP-emulated traffic indicate that the our proposed system together with the benefits of MPTCP improve IoT application performance. More specifically, multipath-based M2M data traffic offloading increases throughput and significantly reduces latency of CoAP requests as the number of sensor networks increases.

Exploiting Client Inference in Multipath TCP Over Multiple Cellular Networks

In this article, we present a client-based multipath TCP (cMPTCP) framework that can cope with path heterogeneity across multiple LTE networks deployed by different operators. cMPTCP is the first work to apply the mobile client's inference based on our observation that an out-of-order queue in an MPTCP receiver (i.e., mobile client) builds up with increasing heterogeneity between different subflows and can significantly degrade throughput performance compared to that achieved by single-path TCP via the best path. For agile and accurate control for the existing MPTCP architecture, we argue that mobile clients are the best network entities to infer the bottleneck state of an end-to-end MPTCP connection. Our proposed cMPTCP consists of two main components: client-initiated multipath selection and subflow-level rate control mechanisms. These mechanisms are compatible with the default MPTCP architecture implemented in the Linux kernel. For performance evaluation, we prototype a complete LTE network testbed consisting of mobile phones, LTE base stations, LTE cores, and application servers. Our experimental results confirm that cMPTCP outperforms existing server-side schedulers in practical dynamic channel conditions.

User-Controlled Subflow Selection in MPTCP: A Case Study

It is common to find multiple network interfaces connected to different Internet Service Providers (ISPs) in devices such as smartphones. Multipath TCP (MPTCP) enables TCP connections to use all these network interfaces in a single TCP connection in an application transparent manner. MPTCP schedules traffic of one TCP connection over subflows created over these network interfaces. It is evident that this requires some scheduling policy. There have been some attempts to allow applications to decide on the scheduling policy. However, this violates the application transparency of MPTCP, and applications do not have all the information required to decide on such a policy. In addition, this allows the applications to monopolize the network connection thus posing a security threat as well. We argue that only the owner of the device (the user) has the right to make that policy decision and only the user can make an informed decision on the scheduling policy. For example, the user has the information on the monetary cost of the connections through different interfaces. In this paper we present a mechanism that allows the user to provide hints to the TCP scheduler to alter its scheduling policy. While this is not a mechanism to implement generic scheduling policies, it demonstrates how a user can guide the scheduling policies. As a proof of the concept, we demonstrate how MPTCP scheduler can be influenced to select a less stable and lossy path over a stable path based on a user preference.

MFVL HCCA: A Modified Fast-Vegas-LIA Hybrid Congestion Control Algorithm for MPTCP Traffic Flows in Multihomed Smart Gas IoT Networks

Multihomed smart gas meters are Internet of Things (IoT) devices that transmit information wirelessly to a cloud or remote database via multiple network paths. The information is utilized by the smart gas grid for accurate load forecasting and several other important tasks. With the rapid growth in such smart IoT networks and data rates, reliable transport layer protocols with efficient congestion control algorithms are required. The small Transmission Control Protocol/Internet Protocol (TCP/IP) stacks designed for IoT devices still lack efficient congestion control schemes. Multipath transmission control protocol (MPTCP) based congestion control algorithms are among the recent research topics. Many coupled and uncoupled congestion control algorithms have been proposed by researchers. The default congestion control algorithm for MPTCP is coupled congestion control by using the linked-increases algorithm (LIA). In battery powered smart meters, packet retransmissions consume extra power and low goodput results in poor system performance. In this study, we propose a modified Fast-Vegas-LIA hybrid congestion control algorithm (MFVL HCCA) for MPTCP by considering the requirements of a smart gas grid. Our novel algorithm operates in uncoupled congestion control mode as long as there is no shared bottleneck and switches to coupled congestion control mode otherwise. We have presented the details of our proposed model and compared the simulation results with the default coupled congestion control for MPTCP. Our proposed algorithm in uncoupled mode shows a decrease in packet loss up to 50% and increase in average goodput up to 30%.

EBA: Efficient Bandwidth Aggregation for Connected Vehicles With MPTCP

Multipath TCP (MPTCP) recently emerges as a promising tool to improve the network service to vehicles through transparent aggregation of wireless infrastructures on the Earth (e.g., current terrestrial BSs) and over the air [e.g., unmanned aerial vehicles (UAVs)-based BSs], e.g., using both LTE and WiFi at the same time for a data transfer. Currently, such an approach is challenged by the fast dynamism of wireless link characteristics (e.g., RTT and loss rate) during the handoff between wireless access points under vehicle mobility, which could easily cause Head-of-Line (HoL) blocking at the receiver and significantly lower the overall network performance. The existing solutions generally rely on asynchronous scheduling at the sender to tackle the HoL blocking. However, they fall short in handling the packet losses and excessive delay during the handoff. In this article, we propose a unique MPTCP scheduling scheme named efficient bandwidth aggregation (EBA) to tackle the drawback in current approaches. EBA adaptively enables packet duplication over parallel paths (i.e., redundant scheduling), which can effectively prevent the HoL blocking but losses some bandwidth. Thus, we carefully model the conditions under which packet duplication can improve network performance. We then dynamically turn on and off redundant scheduling based on the modeling to achieve the best bandwidth performance for vehicles. We have implemented EBA inside the current Linux kernel MPTCP and tested it extensively through simulated scenarios. Experimental results show that EBA can effectively enhance the network service for connected vehicles.

A Rent-Seeking Framework for Multipath TCP

Network utility maximization (NUM) for Multipath TCP (MPTCP) is a challenging task, since there is no well-defined utility function for MPTCP [6]. In this paper, we identify the conditions under which we can use Kelly's NUM mechanism, and explicitly compute the equilibrium. We obtain this equilibrium by using Tullock's rent-seeking framework from game theory to define a utility function for MPTCP. This approach allows us to design MPTCP algorithms with common delay and/or loss constraints at the subflow level. Furthermore, this utility function has diagonal strict concavity, which guarantees a globally unique (normalized) equilibrium.

Adaptive subflow allocation for multipath data transmission in mobile edge networks

Multipath data transmission techniques have been proposed to aggregate the resource of multiple heterogeneous access networks to enhance the robustness and throughput of multi-homed mobile devices. The Multipath TCP (MPTCP) protocol has been standardized by the IETF as an extension of conventional TCP, which enables establishing several subflows over multiple interfaces for simultaneous data transmission. However, current implementation of MPTCP only supports static subflow management strategies, which cannot adapt to the changing to network environment. In this paper, we focus on the issues of dynamic subflow management for MPTCP. We present theoretical analysis to the overall throughput of establishing multiple subflows with MPTCP, based on which we propose an adaptive subflow allocation algorithm to determine the proper number of subflows for each network interface to optimize the performance gain. We implement the proposed algorithm, integrate it into the MPTCP Linux Kernel implementation, and evaluate its performance on a wireless network testbed. Extensive experiments show that the proposed allocation algorithm significantly outperforms the existing subflow management strategies with 57% improvement.

Multipath TCP Meets Transfer Learning: A Novel Edge-Based Learning for Industrial IoT

We consider a fifth-generation (5G)-empowered future Industrial IoT (IIoT) networking problem where IIoT machines are capable of communicating and sharing their data networking knowledge gained (and experiences) with other neighboring devices/tools. For such an IIoT setting, deep-learning (DL)-based communication protocols are known to be highly efficient but having a computationally complex training procedure in terms of both time/space and volume of data sets. One solution for such training is to be completed offline for each equipment and machines of IIoT before deployment. A better approach would be to replicate the model from the expert existing machine and implant it into new machines. Such training for the transfer of knowledge can be done by manufacturers using high computational power, even for large-scale DL models. After sufficient training and the desired level of accuracy, the trained machines can be deployed in the smart factory equipment to perform life-long collaborative learning. We design a novel distributed transfer learning (TL) framework to maximize multipath communication networking performance for Industry 4.0 environment. To conduct seamless sharing of knowledge gain by the multipath TCP (MPTCP) agents and tackle retraining issues of DL-based approaches, we investigate TL for MPTCP from the IIoT networking perspective. With relevant insights from transfer and collaborative learning, we develop a distributed TL-MPTCP framework to accelerate the learning efficiency and enhance the performance of newly deployed machines. Our approach is validated with numerical and emulated NS-3 experiments in comparison with the state-of-the-art schemes.

Multipath Communication With Deep Q-Network for Industry 4.0 Automation and Orchestration

In this article, we design a novel multipath communication framework for Industry 4.0 using deep Q-network [1] to achieve human-level intelligence in networking automation and orchestration. To elaborate, we first investigate the challenges and approaches in exploiting heterogeneous networks and multipath communication [e.g., using multipath transmission control protocol (MPTCP)] for the information technology cum operation technology (IT/OT) convergence in Industry 4.0. Based on the novel idea of intelligent and flexible manufacturing, we analyze the technical challenges of IT/OT convergence and then model network data traffics using MPTCP over the converged frameworks. It quantifies the adverse impact of network convergence on the performance for flexible manufacturing. We provide a few proof-of-concepts solutions; however, after a clear understanding of the tradeoffs, we discover the need for experience-driven MPTCP. The simulation result demonstrates that the proposed scheme significantly outperforms the baseline schemes.

Stochastic Optimization of Multipath TCP for Energy Minimization and Network Stability over Heterogeneous Wireless Network

Multipath Transport Control Protocol (MPTCP) is a transport layer protocol that enables multiple TCP connections across various paths. Due to path heterogeneity, it incurs more energy in a multipath wireless network. Recent work presents a set of approaches described in the literature to support systems for energy consumption in terms of their performance, objectives and address issues based on their design goals. The existing solutions mainly focused on the primary system model but did not discourse the overall system performance. Therefore, this paper capitalized a novel stochastically multipath scheduling scheme for data and path capacity variations. The scheduling problem formulated over MPTCP as a stochastic optimization, whose objective is to maximize the average throughput, avoid network congestion, and makes the system more stable with greater energy efficiency. To design an online algorithm that solves the formulated problem over the time slots by considering its min-drift-plus penalty form. The proposed solution was examined under extensive simulations to evaluate the anticipated stochastic optimized MPTCP (so-MPTCP) outcome and compared it with the base MPTCP and the energy-efficient MPTCP (eMPTCP) protocols. Simulation results justify the proposed algorithm''s credibility by achieving remarkable improvements, higher throughput, reduced energy costs, and lower-end to end delay.

Adaptive Decrease Window for BALIA (ADW-BALIA): Congestion Control Algorithm for Throughput Improvement in Nonshared Bottlenecks

The main design goals of the multipath transmission control protocol (MPTCP) are to improve the throughput and share a common bottleneck link fairly with a single-path transmission control protocol (TCP). The existing MPTCP congestion control algorithms achieve the goal of fairness with single-path TCP flows in a shared bottleneck, but they cannot maximize the throughput in nonshared bottlenecks, where multiple subflows traverse different bottleneck links. This is because the MPTCP is designed not to exceed the throughput of a single-path TCP competing in the bottleneck. Therefore, we believe that MPTCP congestion control should have different congestion window control mechanisms, depending on the bottleneck type. In this paper, we propose an adaptive decrease window (ADW) balanced linked adaptation (BALIA) congestion control algorithm that adaptively adjusts the congestion window decrease in order to achieve better throughput in nonshared bottlenecks while maintaining fairness with the single-path TCP flows in shared bottlenecks. The ADW-BALIA algorithm detects shared and nonshared bottlenecks based on delay fluctuations and it uses different congestion window decrease methods for the two types of bottleneck. When the delay fluctuations of the MPTCP subflows are similar, the ADW-BALIA algorithm behaves the same as the existing BALIA congestion control algorithm. If the delay fluctuations are dissimilar, then the ADW-BALIA algorithm adaptively modulates the congestion window reduction. We implement the ADW-BALIA algorithm in the Linux kernel and perform an emulation experiment that is based on various topologies. ADW-BALIA improves the aggregate MPTCP throughput by 20% in the nonshared bottleneck scenario, while maintaining fairness with the single-path TCP in the shared bottleneck scenario. Even in a triple bottleneck topology, where both types of bottlenecks exist together, the throughput increases significantly. We confirmed that the ADW-BALIA algorithm works stably for different delay paths, in competition with CUBIC flows, and with lossy links.

Loss-Aware Throughput Estimation Scheduler for Multi-Path TCP in Heterogeneous Wireless Networks

Multi-path TCP (MPTCP) is increasingly popular with the widespread usage of multihomed devices. MPTCP allows data streams to be delivered across multiple simultaneous connections, providing higher bandwidth aggregation and throughput in comparison with single-path TCP. However, due to the path heterogeneity and packet losses, the occurrence of Out-of-Order (OFO) packets is inevitable for MPTCP. Although many approaches have been proposed to mitigate OFO, most of them focused on compensating path delay differences but not considered the impact of packet loss. In this paper, we take the first step towards analyzing the impact of packet loss on OFO, and propose Loss-Aware Throughput Estimation scheduler, LATE. LATE comprehensively considers each subflow's path characteristics and protocol parameters including Round Trip Time (RTT), congestion window (cwnd), and loss rate, to predict the data amount that can be sent over each subflow at a given time and determine wisely which segments should be allocated to which subflows. Experimental results show that LATE achieves a gain of 5.13% in mean goodput with long-lasting flows while reducing the completion time of short flows by about 26.68% compared to the state-of-the-art scheduler for MPTCP.

Mobility-Aware Seamless Handover With MPTCP in Software-Defined HetNets

In this article, the problem of vertical handover in software-defined network (SDN) based heterogeneous networks (HetNets) is studied. In the studied model, HetNets are required to offer diverse services for mobile users. Using an SDN controller, HetNets have the capability of managing users' access and mobility issues but still have the problems of ping-pong effect and service interruption during vertical handover. To solve these problems, a mobility-aware seamless handover method based on multipath transmission control protocol (MPTCP) is proposed. The proposed handover method is executed in the controller of the software-defined HetNets (SDHetNets) and consists of three steps: location prediction, network selection, and handover execution. In particular, the method first predicts the user's location in the next moment with an echo state network (ESN). Given the predicted location, the SDHetNet controller can determine the candidate network set for the handover to pre-allocate network wireless resources. Second, the target network is selected through fuzzy analytic hierarchical process (FAHP) algorithm, jointly considering user preferences, service requirements, network attributes, and user mobility patterns. Then, seamless handover is realized through the proposed MPTCP-based handover mechanism. Simulations using real-world user trajectory data from Korea Advanced Institute of Science & Technology show that the proposed method can reduce the handover times by 10.85% to 29.12% compared with traditional methods. The proposed method also maintains at least one MPTCP subflow connected during the handover process and achieves a seamless handover.