Concurrent Multipath Transfer Research Articles

Packets distribution over asymmetric paths using concurrent multipath transfer

AbstractConcurrent multipath transfer (CMT) is a transport layer protocol used for transferring data over multiple paths concurrently. In the case of asymmetric paths, the dissimilarity of delay, bandwidth, and loss rate among paths leads to challenges such as out‐of‐order packets, receiver buffer blocking, and throughput reduction. A framework that uses the end‐to‐end delay of paths to distribute the packets over asymmetric paths in ordering policy is proposed. The proposed framework detects network congestion in the assigned path and reduces the congestion window. Furthermore, the proposed framework predicts receiver buffer blocking and deactivates the highest delay path that causes this problem. The simulation results show that the proposed framework achieves highest throughput, lower entropy and lower average application end‐to‐end delay than the previous algorithms.

Reliable PPO-Based Concurrent Multipath Transfer for Time-Sensitive Applications

Reliable PPO-Based Concurrent Multipath Transfer for Time-Sensitive Applications

LERMS: A Low-Latency and Reliable Downlink Packet-Level Encoding Transmission Method in Untrusted 5GA Edge Network.

The increasing demand for end-to-end low-latency and high-reliability transmissions between edge computing nodes and user elements in 5G Advance edge networks has brought new challenges to the transmission of data. In response, this paper proposes LERMS, a packet-level encoding transmission scheme designed for untrusted 5GA edge networks that may encounter malicious transmission situations such as data tampering, discarding, and eavesdropping. LERMS achieves resiliency against such attacks by using 5GA Protocol data unit (PDU) coded Concurrent Multipath Transfer (CMT) based on Lagrangian interpolation and Raptor's two-layer coding, which provides redundancy to eliminate the impact of an attacker's malicious behavior. To mitigate the increased queuing delay resulting from encoding in data blocks, LERMS is queue-aware with variable block length. Its strategy is modeled as a Markov chain and optimized using a matrix method. Numerical results demonstrate that LERMS achieves the optimal trade-off between delay and reliability while providing resiliency against untrusted edge networks.

Delay optimal for reliability-guaranteed concurrent transmissions with raptor code in multi-access 6G edge network

This paper proposes RCMEN, a solution for Concurrent Multipath Transfer (CMT) of Raptor-Coded (RC) Protocol Data Units (PDU) in a Multi-Access 6G Edge Network (MEN) to provide low-latency and reliable transmission for 6G User Equipment (UE) and Data Network (DN). While 3GPP Release 16 aims to improve the reliability of a single service based on CMT, replication-based reliability causes high resource and signaling overhead, and asymmetric bandwidth and latency lead to excessive latency. RCMEN addresses these issues by distributing data across multiple PDU sessions and using a queue-aware variable-block-length Raptor encoder to optimize resource utilization under random arrivals. We analyze RCMEN’s delay-reliability performance using the Constrained Markov Decision Process (CMDP), reliability is guaranteed by the reliability function, which takes the amount of data sent as a parameter. Through Linear Programming, we obtain the optimal delay-reliability trade-off and optimize delay metrics for two classical RCMEN. Experiments show that both classical RCMEN optimize the long-tail distribution of latency while ensuring reliability, with the entire system being compatible with the current 5G network infrastructure.

A Novel Analytical Framework Is Developed for Wireless Heterogeneous Networks for Video Streaming Applications

Due to bandwidth and time limits, delivering high-quality video streaming facility offers real-time wireless networks, but assuring quality of experience (QoE) is rather difficult. A network host can deliver its data stream via numerous different network pathways. At the same time, using multipath data transmission, where video streaming may be supplied through Internet protocols (IPs) as well as broadband with bidirectional communication between video sources and consumers, is one way to address this difficult problem. In this work, a novel framework is developed for wireless heterogeneous networks for video streaming applications using concurrent multipath transfer (CMT). The performance of frame-level delay can be enhanced for better video quality using this proposed method. The network congestion on end-to-end path utilised in CMT is not dependent of one another, and we operate under prior assumption that receiver’s announced window does not limit the sender. The analytical results show that the proposed framework outperforms existing methods in terms of performance with minimum retransmission delay.

DB-CMT: A New Concurrent Multi-path Stream Control Transport Protocol

Stream Control Transmission Protocol (SCTP) exploits multiple network interfaces to provide multi-streaming and data chunk ordering in a stream. An extended feature of SCTP, i.e., Concurrent Multi-path Transfer (CMT), bids concurrent data transmission in a multi-path data transfer environment and guarantees bandwidth aggregation, load sharing, robustness, and reliability. In such an environment, the paths usually have distinct characteristics (i.e., delay, Packet Loss Rate (PLR), and bandwidth). Thus, data chunks are received out-of-ordered at the destination. As a result, CMT causes excessive receiver buffer blocking and unnecessary congestion window (cwnd) reductions. Also, during the selection of the retransmission destination path (to resend a lost data chunk), CMT does not take into account vital Quality of Service (QoS) parameters such as the PLR of a path under consideration. This paper introduces a new Delay-Based Concurrent Multi-path Transfer (DB-CMT) approach that transmits data on multiple paths according to their delay. In this scheme, we present a Delay-Based Data chunk Scheduling Policy (DB-DSP), a Retransmission Path Selection Policy (RTX-CL), and a new Delay-Based Fast Retransmission Policy (DB-FRP). The simulation results show that the DB-CMT’s RTX-CL policy performs better than the well-known RTX-CWND and RTX-LOSSRATE retransmission schemes. Also, the overall performance of DB-CMT witnesses improved throughput, fewer timeouts, and reduced File Transfer Time (FTT) performances.

Deep reinforcement learning-based fountain coding for concurrent multipath transfer in high-speed railway networks

Deep reinforcement learning-based fountain coding for concurrent multipath transfer in high-speed railway networks

Path-Rank-Based Data Chunk Scheduling for Concurrent Multipath Transmission

Abstract The device equipped with a multi-homing feature optimally exploits multiple network interfaces in modern communications networks such as the Internet of Things (IoT) and machine-to-machine communication using the concurrent multipath transfer (CMT). This enhances system performance by concurrently scheduling data chunks on multiple network paths. For a while, several scheduling criteria have been developed to optimize performance. However, it has been identified that CMT still suffers from many serious problems, such as spurious retransmission, receiver buffer blocking, improper congestion window (CWND) growth, re-ordering and long round trip time, resulting in poor performance. These problems occur due to the asymmetric nature of path characteristics. Thus, this paper introduces a path rank-based CMT (R-CMT) that schedules data chunks according to the rank of the path. The proposed scheduling method calculates the rank of each network path based on the ratio of successfully received and transmitted chunks. The simulation results indicate that the proposed R-CMT scheduling achieves higher performance in terms of network latency, throughput and CWND growth.

An Adaptive CMT-SCTP Scheme: A Reinforcement Learning Approach

With the continuous increase of end users and types of services, the scale of the network has shown explosive growth, which has brought tremendous pressure and challenges to network data transmission. How to achieve high-quality data transmission has become a core issue. Single-path transmission has been difficult to meet the above requirements. The concurrent multipath transfer extension for stream control transmission protocol (CMT-SCTP), which supports multipath and independent data streams, can solve this problem. However, the current transmission path assessment scheme has too large granularity to make full use of the resources of the transition zone. Most studies ignore the different requirements of different services, a single transmission strategy, and the lack of an intelligent dynamic adjustment mechanism. Therefore, we designed a QCMT(Q-learning based CMT-SCTP) scheduling method. This method considers the multi-dimensional characteristics of the path and the characteristic preferences of different services, periodically evaluates and trains the reinforcement learning model for service adaptation, and makes scheduling decisions dynamically. Experimental results show that dynamic scheduling based on path parameters and service preferences can reduce message delay and improve network throughput.

Reliable Cybertwin-Driven Concurrent Multipath Transfer With Deep Reinforcement Learning

It is well known that concurrent multipath transfer (CMT) can improve the transmission rate. However, due to multiple heterogeneous paths from users to the access network, a large number of out-of-order packets significantly degrade the overall transmission reliability. Cybertwin provides a potential solution to alleviate the packet out-of-order problem by accurately detecting and perceiving the path state. In this article, we investigate the data scheduling problem and propose a learning-based cybertwin-driven CMT algorithm to obtain the optimal data scheduling policy. In particular, we first formulate the data scheduling problem as an integer linear programming by taking the QoS metrics into account. To cope with the packet out-of-order problem in CMT, we propose a reliable cybertwin-CMT with deep reinforcement learning (CMT-DRL) algorithm to determine the data scheduling decisions. The proposed algorithm takes multipath throughput, end-to-end delay, and packet loss rate into account. Besides, CMT-DRL adopts an asynchronous learning framework to efficiently execute data collection, packet scheduling, and neural network training in sequence by decoupling model training and execution. We conduct extensive experiments in a P4-based programmable network platform. Experimental results indicate that the CMT-DRL outperforms the existing benchmarks in terms of the number of out-of-order packets, round-trip time, and throughput.

Flowlet-Based Stateful Multipath Forwarding in Heterogeneous Internet of Things

Concurrent multipath transfer effectively improves network throughput and reliability by utilizing the unoccupied network links. However, the performance of concurrent multipath transfer degrades significantly in the heterogeneous Internet of Things. The reason is that the disorder and retransmission will increase sharply if the quality of links are greatly different. This paper proposes a multipath stateful forwarding mechanism in the granularity of flowlet, which is featured with planning the flowlet forwarding dynamically to improve the transmission success rate. Besides, our mechanism implements stateful forwarding by improving the state information processing capability of the data plane. It can adjust the size of the flowlet based on the network performance of the path, thereby improving the bandwidth resource utilization of the system. In particular, the proposed mechanism can sense network congestion status dynamically, detect network anomalies, and re-plan the forwarding strategy. Experimental results show that in the harsh environment (link quality varies greatly among the three test paths), the proposed mechanism can improve the throughput by 114.7% and reduce the percentage of out of order packets by 29.5% compared with the Round-Robin Scheduling mechanism.

Energy-Efficient Multipath TCP for Quality-Guaranteed Video Over Heterogeneous Wireless Networks

Prompted by technological advancements in wireless systems and handheld devices, concurrent multipath transfer is a promising solution to stream high-quality mobile videos in heterogeneous access medium. Multipath TCP (MPTCP) is a transport-layer protocol recommended by the Internet Engineering Task Force (IETF) for concurrent data transmission to multi-radio terminals. However, it is still challenging to stream high-quality real-time videos with the existing MPTCP solutions because of the tradeoff between energy efficiency and video quality. To deliver real-time video in an energy-efficient manner, this paper presents a Delay-Energy-quAlity-aware MPTCP (DEAM) solution. First, an analytical framework is developed to characterize the delay-constrained energy–quality tradeoff for multipath video delivery over heterogeneous access networks. Second, a subflow allocation algorithm is proposed to minimize the device energy consumption while achieving target video quality within the imposed deadline. The performance of the proposed DEAM is verified by means of extensive Exata emulations with real-time streaming videos. Evaluation results demonstrate that DEAM achieves appreciable improvements over the reference MPTCP solutions in mobile energy conservation and user-perceived video quality.

Handover optimisation for multipath transmission control protocol‐based concurrent multipath transfer in heterogeneous networks

In this Letter, the authors propose a handover optimisation scheme (HOS) for multipath transmission control protocol-based concurrent multipath transfer in heterogeneous networks. HOS includes two sections, proactive packet scheduling and access network selection. The former one proactively stops scheduling packets to the subflow about to be switched in order to reduce out-of-order packets during handover, while the latter one aims to select the optimal network for handover from multiple candidate networks by jointly considering multiple influential factors, i.e. path quality and dwelling time. Simulation results verify the effectiveness of the proposed scheme, which can achieve relatively higher throughput with fewer handovers.

Loss-Aware CMT-Based Multipathing Scheme for Efficient Data Delivery to Heterogeneous Wireless Networks

With the rapid development of wireless networks, multiple network interfaces are gradually being designed into more and more mobile devices. When it comes to data delivery, Stream Control Transmission Protocol (SCTP)-based Concurrent Multipath Transfer (CMT) has proven to be quite useful solution for multiple home networks, and it could become the key transport protocol for the next generation of wireless communications. The CMT delay caused by data rearrangement has been noticed by researchers, but they have seldom considered the frequent occurrence of packet loss that occurs in the high-loss networks. In this paper, we proposed an original loss-aware solution for multipath concurrent transmission (CMT-LA) that achieves the following goals: (1) identifying packet loss on all paths, (2) distributing packets adaptively across multiple available paths according to their packet loss and loss variation, and (3) maintaining the features of bandwidth aggregation and parallel transmission of CMT while improving the throughput performance. The results of our simulations showed that the proposed CMT-LA reduces reordering delay and unnecessary fast retransmissions, thereby demonstrating that CMT-LA is a more efficient data delivery scheme than classic CMT.

Energy-Aware Concurrent Multipath Transfer for Real-Time Video Streaming Over Heterogeneous Wireless Networks

The advancements in networking technologies and hand-held devices enable mobile users to concurrently receive real-time multimedia streaming (e.g., high-definition video) with different radio interfaces (e.g., Wi-Fi and LTE networks). Stream control transmission protocol (SCTP) is an important transport-layer solution to implement concurrent multipath transfer (CMT) over heterogeneous wireless networks with multihomed terminals. However, it is challenging to distribute multimedia content to resource-limited mobile devices because of the contradiction between energy consumption and streaming quality. To deliver the energy-efficient and quality-aware multimedia streaming over multiple wireless networks, this paper presents an Energy and goodPut Optimized CMT (EPOC) solution. First, we develop an analytical framework to model the relationship between energy consumption and goodput performance for real-time multimedia transmission to multihomed mobile devices. Second, we propose a joint forward error correction coding and rate allocation scheme to minimize energy consumption while satisfying goodput constraint. EPOC effectively leverages the energy-goodput tradeoff and multipath diversity to optimize mobile multimedia transmission in heterogeneous networking environment. We conduct the performance evaluation through extensive semi-physical emulations in Exata involving H.264 video streaming. Compared with the reference CMT schemes using SCTP, EPOC achieves appreciable improvements in energy conservation, goodput, and video peak signal-to-noise ratio.

Using multiple paths in SCTP to reduce latency for signaling traffic

The increase in traffic volumes as well as the heterogeneity in network infrastructure in the upcoming 5G cellular networks will lead to a dramatic increase in volumes of control traffic, i.e., signaling traffic, in the networks. Moreover, the increasing number of low-power devices with an on-off behavior to save energy will generate extra control traffic. These increased traffic volumes for signaling traffic, often generated as bursts of messages, will challenge the signaling application timing requirements on transmission. One of the major transport protocols deployed for signaling traffic in cellular networks is the Stream Control Transmission Protocol (SCTP), with support for multiple paths as well as for independent data flows. This paper evaluates transmission over several paths in SCTP to keep the latency low despite increasing traffic volumes. We explore different transmission strategies and find that concurrent multipath transfer over several paths will significantly reduce latency for transmission over network paths with the same or similar delay. Still, over heterogeneous paths, careful, continuous sender scheduling is crucial to keep latency low. To this end, we design and evaluate a sender scheduler that considers path characteristics as well as queuing status and data flows of different priority to make scheduling decisions. Our results indicate that by careful dynamic sender scheduling, concurrent multipath transfer could lead to reduced latency for signaling traffic irrespective of path or traffic characteristics.

Analysis of Retransmission Policies for Parallel Data Transmission

Stream control transmission protocol (SCTP) is a transport layer protocol, which is efficient, reliable, and connection-oriented as compared to transmission control protocol (TCP) and user datagram protocol (UDP). Additionally, SCTP has more innovative features like multihoming, multistreaming and unordered delivery. With multihoming, SCTP establishes multiple paths between a sender and receiver. However, it only uses the primary path for data transmission and the secondary path (or paths) for fault tolerance. Concurrent multipath transfer extension of SCTP (CMT-SCTP) allows a sender to transmit data in parallel over multiple paths, which increases the overall transmission throughput. Parallel data transmission is beneficial for higher data rates. Parallel transmission or connection is also good in services such as video streaming where if one connection is occupied with errors the transmission continues on alternate links. With parallel transmission, the unordered data packets arrival is very common at receiver. The receiver has to wait until the missing data packets arrive, causing performance degradation while using CMT-SCTP. In order to reduce the transmission delay at the receiver, CMT-SCTP uses intelligent retransmission polices to immediately retransmit the missing packets. The retransmission policies used by CMT-SCTP are RTX-SSTHRESH, RTX-LOSSRATE and RTX-CWND. The main objective of this paper is the performance analysis of the retransmission policies. This paper evaluates RTX-SSTHRESH, RTX-LOSSRATE and RTX-CWND. Simulations are performed on the Network Simulator 2. In the simulations with various scenarios and parameters, it is observed that the RTX-LOSSRATE is a suitable policy.

Video Quality Assessment for Concurrent Multipath Transfer

Video Quality Assessment for Concurrent Multipath Transfer

A Performance Analysis Model of TCP over Multiple Heterogeneous Paths for 5G Mobile Services

Driven by the primary requirement of emerging 5G mobile services, the demand for concurrent multipath transfer (CMT) is still prominent. Yet, multipath transport protocols are not widely adopted and CMT schemes based on Transport Control Protocol (TCP) will still be in dominant position in 5G. However, the performance of TCP flow transferred over multiple heterogeneous paths is prone to the link quality asymmetry, the extent of which was revealed to be significant by our field investigation. In this paper, we present a performance analysis model for TCP over multiple heterogeneous paths in 5G scenarios, where both bandwidth and delay asymmetry are taken into consideration. The evaluation using large-scale simulation and field experiment shows that the proposed model can achieve high accuracy in practical environments. Some interesting inferences can be drawn from the proposed model, such as the dominant factors that affect the performance of TCP over heterogeneous networks, and the criteria of determining the appropriate number of links to be used under different circumstances of path heterogeneity. Thus, the proposed model can provide a guidance to the design of TCP-based CMT solutions for 5G mobile services.

The Minimum Relative Delay First Strategy for Multipath Transmission

The Stream Control Transmission Protocol (SCTP) [1] is a transport protocol which was proposed and standardized by the Internet Engineering Task Force (IETF). The Concurrent Multipath Transfer (CMT) that was evolved based on SCTP’s multi-homing feature had become a hot research issue. CMT utilizes all available paths inside the SCTP association to further improve end to end throughput and fault tolerance capacity during the data transmission. Since the typical scheduling algorithms define how to schedule multi-streaming and multi-homing fixedly, the CMT cannot meet the speific requirements of different applications which limits the felxibility of the transmission protocol. Firstly, this paper introduced four kinds of scheduling algorithms, then a Minimum Ralative Delay First (MRDF) strategy was proposed to compare the relative one way delay of different paths without clock synchronisation. The NS2 simulation platform operated in Linux virtual machine is adopted to compare the system performance.