Multipath Transmission Scheme Research Articles

Fountain code-based multipath reliable transmission scheme with RNN-assisted predictive feedback

Fountain code-based multipath reliable transmission scheme with RNN-assisted predictive feedback

Secure optical communication system based on polarization regulation of the data fragmentation multipath transmission technology.

We propose and demonstrate a data fragment multipath transmission scheme to achieve a secure optical communication based on polarization regulation. A dual-polarization Mach-Zehnder modulator (DPMZM) is driven by digital signals which are scattered by field-programmable gate array (FPGA) and transmitted in multiple paths. By utilizing two orthogonal polarization states, we have achieved a signal transmission under different optical parameters, and the transmission rate of the two paths can reach over 10 Gbps through a 20 km fiber with 2.5 Gbps hopping rate. In addition, we establish a theoretical model to analyze the security of the system and simulate brute force cracking; the probability of cracking the minimum information unit is 1.53 × 10-53. This proves that it is difficult to obtain a user data even using the fastest computers. Our scheme has provided, to our knowledge, a new approach for physical layer security.

Fine-grained load balancing with proactive prediction and adaptive rerouting in data center

Though the existing load balancing designs successfully make full use of available parallel paths and attain high bisection network bandwidth, they reroute flows regardless of their dissimilar performance requirements. But traffic in modern data center networks exhibits short bursts characteristic, which can easily lead to network congestion. The short flows suffer from the problems of large queuing delay and packet reordering, while the long flows fail to obtain high throughput due to low link utilization and packet reordering. In order to solve these inefficiency, we designed a fine-grained load balancing method (FLB), which uses an active monitoring mechanism to split traffic, and flexibly transfers flowlet to non-congested path, effectively reducing the negative impact of burst flow on network performance. Besides, to avoid packet reordering, FLB leverages the probe packets to estimate the end-to-end delay, thus excluding paths that potentially cause packet reordering. The test results of NS2 simulation show that FLB significantly reduces the average and tail flow completion time of flows by up to 59% and 56% compared to the state-of-the-art multi-path transmission scheme with less computational overhead, as well as increases the throughput of long flow.

Deep reinforcement learning‐based joint task offloading and resource allocation in multipath transmission vehicular networks

AbstractMobile edge computing (MEC) is increasingly being applied to task computation with the continuing increase of computing‐intensive applications in vehicular networks. The MEC can offload the tasks generated by the vehicle to the MEC server to mitigate the computational constraints on the mobile vehicle. However, most task offloading algorithms can not cope with the dynamic distribution of vehicles in vehicular networks. Moreover, most task offloading algorithms do not consider vehicular networks using multipath transmission schemes. Therefore, it remains a challenge to implement efficient joint task offloading and resource allocation (JTORA) algorithms in multipath transmission vehicular networks. In this paper, we introduce a novel cooperative transmission network architecture in multipath transmission vehicular networks. The computational tasks generated by the vehicles can be offloaded to MEC servers deployed near the base station or to cloud servers via multipath transmission. We formulate the task offloading and resource allocation problem as a multi‐objective optimization problem in a multipath transmission vehicular network. To achieve efficient task offloading and resource allocation under cooperative transmission network architecture, we propose a JTORA algorithm for multipath transmission vehicular networks based on deep reinforcement learning (DRL). JTORA converts the optimization problem into a DRL model and obtains a specific optimization policy through model training. Simulation results show that JTORA achieves lower average task delay and lower average task cost than other traditional heuristic algorithms.

A Novel Multipath Transmission Scheme for Information-Centric Networking

Due to the overload of IP semantics, the traditional TCP/IP network has a number of problems in scalability, mobility, and security. In this context, information-centric networking (ICN) is proposed to solve these problems. To reduce the cost of deployment and smoothly evolve, the ICN architecture needs to be compatible with existing IP infrastructure. However, the rigid underlying IP routing regulation limits the data transmission efficiency of ICN. In this paper, we propose a novel multipath transmission scheme by utilizing the characteristics and functions of ICN to enhance data transmission. The process of multipath transmission can be regarded as a service, and a multipath transmission service ID (MPSID) is assigned. By using the ICN routers bound to the MPSID as relay nodes, multiple parallel paths between the data source and the receiver are constructed. Moreover, we design a path management mechanism, including path selection and path switching. It can determine the initial path based on historical transmission information and switch to other optimal paths according to the congestion degree during transmission. The experimental results show that our proposed method can improve the average throughput and reduce the average flow completion time and the average chunk completion time.

Reducing tail latency with coding-based packet spraying in edge datacenters

Modern cloud computing applications have stringent low-latency and high-throughput requirements to meet the increasingly diverse demands from customers. In edge datacenters, the popular load balancing scheme based on packet spraying, i.e., random packet spraying (RPS), makes good use of multiple equal-cost paths to ensure high link utilization and efficient transmission. However, RPS performs poorly under the bursty traffic scenario due to packet loss or even timeout. Therefore, to reduce the tail latency caused by retransmission, we design a coding-based random packet spraying named CRPS. Specifically, the source host transmits forward error correction (FEC) encoded packets and dynamically adjusts the data redundancy based on the packet loss rate. Then the switch randomly sprays the encoded packets across all equal-cost multiple paths to implement parallel transmission. In this way, once enough encoded packets from any parallel paths arrive at the destination host, the original packets can be decoded immediately to address the adverse impact of packet loss. The NS-2 simulation results show that CRPS effectively reduces the probability of timeout and significantly improves the tail flow completion time (FCT) by up to 72% compared with the state-of-the-art multipath transmission schemes.

An SDN-Coordinated Steering Framework for Multipath Big Data Transfer Application

Data Transmission is a primary mechanism that can affect the performance of distributed storage systems. The traditional single-path transmission protocols are not efficient to serve several requirements of big data applications. In this paper, we propose an SDN-coordinated steering framework for multipath big data transfer applications. Multipath TCP protocol (MPTCP) coupled with SDN are mainly used for big data transfer in our framework. This framework is useful and cost-effective for OpenFlow networks and overlay networks. To provide a practical multipath transmission scheme for big data transfer applications using MPTCP, we propose a novel OpenFlow-Stats routing algorithm. In our algorithm, a new topology-pruning technique is applied, and the transmission paths are selected based on switch-port statistics. Our proposed framework is implemented and evaluated using the Mininet emulator and ONOS controller. The results show that our routing scheme can reduce the completion time of big data transfer up to 90% compared with the traditional routing with disjoint paths and up to 35% compared with the previous work. Moreover, our proposed routing is more scalable than other previous works in that it can provide lower complexity and system overhead. The results show that our routing scheme produces 57% less overhead compared with the previous work.

Improve the reliability of 6G vehicular communication through skip network coding

One important design goal of 6G networks is adapting to complex heterogeneous scenarios and providing a stable and reliable transmission channel for specific applications such as vehicular communication. To achieve this, scholars attempt to use heterogeneous wireless networks around a vehicle to improve the reliability of 6G network transmission through multipath transmission schemes and network coding schemes. However, the wireless networks around the vehicle may experience burst consecutive loss due to wireless channel fluctuations. Currently, the classic multipath transmission schemes and network coding schemes may not be able to deal with such packet loss in time, which affects the reliability of transmission.In this paper, we propose a skip network coding (SNC) multipath transmission scheme that draws on the idea of interleaving, which groups and encodes discrete packets that meet the interleaving distance. SNC can decrease burst consecutive loss without packet reordering issues to improve transmission performance. In addition, we provide the algorithmic implementation details of SNC. Finally, we design a vehicular communication multipath transmission simulation system based on network simulation 3 (NS-3) and verify that the universality of SNC multipath transmission schemes in mobile scenarios is superior to current multipath transmission schemes.

An integrated blockchain network with energy router-based trading strategy for optimal energy management

The new emerging idea of energy router and energy blockchain network (EBN) is gaining remarkable attention due to various applications and innovative solutions for efficient energy trading. However, the implementation of the EBN raises multiple challenges such as lack of power loss consideration and congestion management, insufficient computing, and higher transaction costs. This paper introduces a new energy trading approach to counter energy trading challenges effectively and perform optimal energy trading. The proposed systematic design was divided into four steps which execute (i) forming trading pairs through a two-stage Stackelberg game model, (ii) checking security by using the characteristics of directional power flow, (iii) congestion management through the minimum loss multi-path power transmission scheme, (iv) forming smart contracts, and settling transactions. The performance of the proposed framework is verified using 13 nodes EBN implementation, where the results obtained demonstrate accurate energy trading, balanced trading prices, even in congestion conditions.

BSS: A Burst Error-Correction Scheme of Multipath Transmission for Mobile Fog Computing

In the scenario of mobile fog computing (MFC), communication between vehicles and fog layer, which is called vehicle-to-fog (V2F) communication, needs to use bandwidth resources as much as possible with low delay and high tolerance for errors. In order to adapt to these harsh scenarios, there are important technical challenges concerning the combination of network coding (NC) and multipath transmission to construct high-quality V2F communication for cloud-aware MFC. Most NC schemes exhibit poor reliability in burst errors that often occur in high-speed movement scenarios. These can be improved by using interleaving technology. However, most traditional interleaving schemes for multipath transmission are designed based on round robin (RR) or weighted round robin (WRR), in practice, which can waste a lot of bandwidth resources. In order to solve those problems, this paper proposes a novel multipath transmission scheme for cloud-aware MFC, which is called Bidirectional Selection Scheduling (BSS) scheme. Under the premise of realizing interleaving, since BSS can be used in conjunction with a lot of path scheduling algorithms based on Earliest Delivery Path First (EDPF), it can make better use of bandwidth resources. As a result, BSS has high reliability and bandwidth utilization in harsh scenarios. It can meet the high-quality requirements of cloud-aware MFC for transmission.

APS: Adaptive Packet Spraying to Isolate Mix-Flows in Data Center Network

Modern data centers host diverse applications, which generate a mix of short flows with stringent latency requirement and long flows requiring large sustained throughput. To solve the problem of resource competition between the mixed flows, we propose an adaptive traffic isolation scheme APS. Based on the packet spraying scheme in the multipath transmission, APS dynamically separates long flows from short ones on different paths to provide the low latency for the short flows. Meanwhile, to resolve the out-of-order problem, APS limits the long flows to a few paths with Equal Cost Multi Path (ECMP). Experimental results of NS2 simulation and testbed implementation show that, APS reduces the average completion time for short flows by up to 60 percent and increases the throughputs for long flows by about 1.68x over the state-of-the-art multipath transmission schemes.

CAPS: Coding-Based Adaptive Packet Spraying to Reduce Flow Completion Time in Data Center

Modern data-center applications generate a diverse mix of short and long flows with different performance requirements and weaknesses. The short flows are typically delay-sensitive but to suffer the head-of-line blocking and out-of-order problems. Recent solutions prioritize the short flows to meet their latency requirements, while damaging the throughput-sensitive long flows. To solve these problems, we design a Coding-based Adaptive Packet Spraying (CAPS) that effectively mitigates the negative impact of short and long flows on each other. To exploit the availability of multiple paths and avoid the head-of-line blocking, CAPS spreads the packets of short flows to all paths, while the long flows are limited to a few paths with Equal Cost Multi Path (ECMP). Meanwhile, to resolve the out-of-order problem with low overhead, CAPS encodes the short flows using forward error correction (FEC) technology and adjusts the coding redundancy according to the blocking probability. Moreover, since the coding efficiency decreases when the coding unit is too small or large, we demonstrate how to obtain the optimal size of coding unit. The coding layer is deployed between the TCP and IP layers, without any modifications on the existing TCP/IP protocols. The test results of NS2 simulation and small-scale testbed experiments show that CAPS significantly reduces the average flow completion time of short flows by ~30%–70% over the state-of-the-art multipath transmission schemes and achieves the high throughput for long flows with negligible traffic overhead.

BNNC: Improving Performance of Multipath Transmission in Heterogeneous Vehicular Networks

Nowadays, multipath transmission scheme in heterogeneous vehicular networks has become an emerging topic. It is a great challenge to overcome the unreliability of heterogeneous wireless network in vehicle-to-ground multipath communication. Many multipath transmission schemes were proposed. However, most schemes do not consider the unreliability of wireless networks and are difficult to deploy in vehicle-to-ground communications. Even though part of the multipath transmission schemes consider the unreliability of wireless networks, their overhead is too large to be deployed in vehicle-to-ground multipath communication. Therefore, we propose a BigNum Network Coding (BNNC) scheme for vehicle-to-ground multipath communication. Compared with the Opportunistic Routing (OR) scheme, BNNC's network resource overhead is smaller. Compared with other network coding schemes, it is a better trade-off between coding flexibility and codec efficiency. In this paper, we propose a brand-new mathematical model for network coding which can effectively improve the reliability of the vehicular networks. Secondly, based on the mathematical model, we design BNNC multipath transmission scheme. Compared with the current network coding scheme, the BNNC scheme considers coding flexibility and codec efficiency while ensuring multipath transmission reliability. Thirdly, we compare BNNC scheme with many current multipath transmission schemes through lots of simulations and real tests. The results show that the BNNC scheme is significantly superior to the other network coding schemes in terms of computational performance. And in terms of the network performance, the BNNC scheme can overcome the unreliability of wireless networks in multipath transmission and it has lower overhead than OR scheme.

Buffer-Driven Rate Control and Packet Distribution for Real-Time Videos in Heterogeneous Wireless Networks

Video transmission bandwidth can be substantially increased by concurrent transmission through multiple radio interfaces introduced by heterogeneous wireless networks. However, delivering high-quality real-time videos with stringent end-to-end delay constraints is still challenging due to the time-varying multipath channel status. Thus, to integrate available multipath bandwidth and guarantee low end-to-end delay, this paper investigates a real-time concurrent multipath video transmission scheme in heterogeneous access networks. First, we present a multipath buffer analysis model (MBAM) to derive the lower and upper bounds of the target video frame bits. Second, given the low-latency and received video quality smoothness, we propose a buffer-driven rate control and packet distribution (BRCPD) algorithm aided by frame-level rate control and multipath transmission buffer awareness based on MBAM. Finally, we implement the proposed application-layer solution BRCPD algorithm in a real-world testbed. The experiment results verify that different from existing multipath video transmission schemes, the proposed algorithm is able to leverage the MBAM-based frame-level rate control to guarantee the target low end-to-end delay. In particular, the BRCPD algorithm is able to guarantee an overdue loss rate of less than 5% under strictly limited delay constraints (250 ms) in the real-world testbed.

An Adaptive Multipath Algorithm to Overcome the Unpredictability of Heterogeneous Wireless Networks for High-Speed Railway

Accessing Internet services in high-speed mobile scenario is an increasing demand for passengers and vendors. Owing to the bandwidth limitation of a single wireless network, researchers attempt to utilize the heterogeneous wireless networks along tracks to achieve multipath parallel transmission. These multipath transmission schemes usually depend on the accurate estimation of network quality to achieve high performance. However, due to the unpredictability of wireless networks in high-speed mobile scenario, current multipath transmission schemes perform poorly. In this paper, first, we make quantitative analysis for the unpredictability of wireless networks. With lots of results of real experiments, we make quantitative analysis for the estimation error of classical algorithms in different scenarios. Second, aiming at the unpredictability of wireless networks, we propose a multipath transmission algorithm named receiver adaptive incremental delay (RAID) that can aggregate bandwidth for heterogeneous networks independent of accurate network quality estimation. Final, we deploy the RAID algorithm into a real system. Abundant of real experiments and simulations prove that our proposed algorithm has a better performance than the earliest completion first algorithm and the weighted round Robin (WRR) algorithm in high-speed mobile scenario.

Secure free-space optical communication system based on data fragmentation multipath transmission technology.

A secure free-space optical (S-FSO) communication system based on data fragmentation multipath transmission (DFMT) scheme is proposed and demonstrated for enhancing the security of FSO communications. By fragmenting the transmitted data and simultaneously distributing data fragments into different atmospheric channels, the S-FSO communication system can protect confidential messages from being eavesdropped effectively. A field experiment of S-FSO communication between two buildings has been successfully undertaken, and the experiment results demonstrate the feasibility of the scheme. The transmission distance is 50m and the maximum throughput is 1 Gb/s. We also established a theoretical model to analysis the security performance of the S-FSO communication system. To the best of our knowledge, this is the first application of DFMT scheme in FSO communication system.

Elastic Resource Allocation for Multi-Granularity Multicasting Traffic in OFDM-Based Optical Networks

With the increasing requirements of the multicast services in the whole data traffic service, the optical multicast technology becomes a key technology supporting wide bandwidth and high speed multicasting communication. The transmission efficiency, capacity and robustness of optical multicast network can be further improved by introducing network coding technology into optical multicast networks. Meanwhile, facing to demand of emerging rate-variable multi-granularity multicast service, a multi-path transmission scheme based on network coding for routing and spectrum allocation (RSA) is proposed. It can not only allocate spectrum resources effectively and flexibly for various-rate multicast traffic, but also balance the network load, improve network throughput and reduce transmission blocking rate. In this paper, RSA problem is decomposed into two subproblems, namely routing allocation based on network coding and spectrum allocation based on maximum spectrum first (MSF) strategy, which are solved sequentially. Simulation experiments are carried out to analyze transmission performance with proposed RSA scheme. The simulation results show that the proposed RSA mechanism can allocate spectrum resources efficiently and flexibly for multi-granularity multicast traffic. Compared with RSA schemes based on shortest path tree (SPT) and minimal spanning tree (MST), the proposed RSA scheme is more efficient for spectrum resource utilization and load balancing, and spectrum resource is saved more than 20%.

Deterministic Time Markov Chain Modelling of Simultaneous Multipath Transmission Schemes

The increase in the availability of multimode devices for ubiquitous network access and the need for larger bandwidth have created a thrust for the utilization of simultaneous network connections. Unfortunately, the standard transport layer protocols such as the transmission control protocol and user datagram protocol have structural constraints. As a result, an Internet application can use only one interface at a time. The stream control transmission protocol (SCTP) provides support for concurrent multipath transfer (SCTP-CMT). In this paper, we present the mathematical modeling of simultaneous multipath transmission (SMT) schemes using the deterministic time Markov chain (DTMC) model. In this DTMC model, receiver buffer size is used for the first time to estimate the sending data rate. The DTMC model of SMT schemes are compared with the SCTP-CMT using probability-based packet dropped scenarios. DTMC modeling is used to mathematically verify simulation results of SMT Schemes i.e., modified fast retransmit (SMT-MFR) and adaptive modified fast retransmit (SMT-AMFR). The analytical model results revealed that SMT-MFR outperformed SCTP-CMT by 8.54% gain in average throughput. SMT-AMFR outperformed the SCTP-CMT and SMT-MFR by 19.65% and 11.15% gain in average throughput, respectively.

Improving Onboard Internet Services for High-Speed Vehicles by Multipath Transmission in Heterogeneous Wireless Networks

With the development of modern high-speed vehicles and mobile communication systems, there is a strong demand for operators to provide stable and high-quality onboard Internet services. However, the vehicle-to-ground links may suffer from several problems, such as insufficient bandwidth and long round-trip time (RTT). Although multiple wireless networks, such as Wi-Fi, third-generation (3G), and fourth-generation (4G), may be available along a track, onboard users do not have good experiences if they can only visit the Internet via one wireless network, which may be subject to coverage gaps and signal attenuation. In this paper, the link qualities of multiple existing 3G and 4G technologies are first measured in a typical high-speed environment. These 3G/4G networks are candidates for vehicle-to-ground communication. Then, a concurrent multipath transmission scheme, together with a network adaptive scheduling algorithm, is proposed. The scheme is independent of the protocol stack; therefore, it is easy to deploy. It also provides transparent Internet services for users, without requiring the participation of the user devices in any multipath signaling. Meanwhile, the scheduling algorithm works at the network layer, instead of the transport layer, to meet the diverse transmission requirements of the connection-oriented and connectionless user applications. The algorithm can effectively aggregate the bandwidth of multiple available wireless links, as well as avoid the reordering of packets based on both the practical tracing databases and the active path monitoring. Analysis and experiments show that the proposed algorithm can provide better onboard Internet services with lower cache requirements than the Earliest Delivery Path First (EDPF) and Weighted Round Robin (WRR) scheduling algorithms, in terms of bandwidth improvement and packet disorder reduction.

CMT-SR: A selective retransmission based concurrent multipath transmission mechanism for conversational video

Conversational video service is characterized by the high bandwidth demand, and the stringent and low delay requirement. High-quality delivery service for conversational video service not only depends on end-to-end bandwidth but also relies on control mechanisms to alleviate the impact of packet loss on video quality. Multipath transmission is considered to be a promising solution to expand end-to-end bandwidth. However, existing multipath transmission schemes are not suitable for conversational video service delivery because they incur either a large number of duplicated packet or a large delay. In this work, retransmission mechanism that satisfies delay requirement is discussed to recover packet loss. The main problem of the retransmission mechanism is the delay. A selective retransmission based concurrent multipath transmission mechanism (CMT-SR) is proposed to optimize the performance of retransmission. Several mechanisms are adopted to retransmit the lost packet in an optimal way. CMT-SR monitors and analyzes the bandwidth and delay of each path, which provides a foundation for estimating arrival time of data packet. Push-based and pull-based mechanisms support sender to be aware of packet loss timely. CMT-SR differentiates between different frames of packet loss. Finally, CMT-SR first retransmits the key parts of the video data over an alternative path considering the decoding deadline, retransmission delay, and characteristic of video streaming. CMT-SR is a reliable multipath transmission scheme for conversational video service and is evaluated by extensive simulations and actual tests. Experimental results show that CMT-SR is an effective way to improve the quality of conversational video service delivery.