Low-delay Communication Research Articles

Data-driven road side unit location optimization for connected-autonomous-vehicle-based intersection control

Low communication delay is crucial for the effectiveness of connected-autonomous-vehicle-based (CAV-based) intersection control strategies. To achieve low vehicle-to-road-side-unit (V2R) communication delay and support the implementation of CAV-based intersection control strategies, this study addresses the problem of road side unit (RSU) location optimization at a single intersection. Considering the uncertainty of the selection of intersection control strategies, the problem is formulated as a two-stage stochastic mixed-integer nonlinear program. The model aims to minimize the sum of the cost associated with RSU investment and the expectation of the penalty cost associated with V2R communication delay exceeding a pre-determined threshold. The first stage of the program determines the number and location of RSUs, when the intersection control strategy to be implemented is unknown. Given the first stage decision and the implemented intersection control strategy, the second stage model optimizes the detection area allocation among RSUs to minimize the penalty cost. The model is linearized using the piecewise linearization technique. Then an integer L-Shaped algorithm is proposed to find a global optimal solution to the linearized program. In the numerical example, the proposed model is compared with a deterministic model. The results demonstrate that the V2R communication reduction per cost obtained by the proposed model is 28.95 larger than that obtained by the deterministic model, in the scenario that a CAV-based control strategy is implemented in the second stage. This indicates that the proposed model provides cost-effective low V2R communication delay for intersection control in CAV environment.

Dynamic bandwidth allocation based on adaptive predictive for low latency communications in changing passive optical networks environment

The industry is considering redesigning the architecture of optical access networks (PONs) to address the challenges of 5G developments. One of the major challenges is to achieve low communication delay. To better address this challenge, PONs not only need to be improved from the perspective of underlying facilities, but also need to combine with effective resource allocation strategies. This paper proposes a dynamic bandwidth allocation strategy based on adaptive predictive algorithm. First, the amount of arriving packets at each ONU during each polling cycle is predicted using the XGBoost ensemble learning algorithm. As such, arriving packets can be allocated bandwidth in advance, so as to achieve low communication delay. Simulations verify that the DBA algorithm based on XGBoost is basically the same as the DBA algorithm based on neural network algorithm in terms of delay performance, but requires less computing time. At the same time, for increasing the robustness of the algorithm, dealing with the changing PONs environment (e.g., the number of ONUs online in PONs changes over time caused by sleep mode), we use dynamic perceptual algorithm which uses the ideas of reinforcement learning to adjust the result of the predictive algorithm, this perceptual algorithm helps to reduce the predictive error caused by environmental changes, so as to reduce the error impact on achieving low delay. Through simulation experiments with different PON environments, the effectiveness of the proposed algorithm is verified and the delay effect of the original predictive algorithm is improved by nearly 10% with the adaptive predictive algorithm.

Network Performance Measurement through Machine to Machine Communication in TeleRobotics System

Machine-to-machine (M2M) communication devices communicate and exchange information with each other in an independent manner to perform necessary tasks. The machine communicates with another machine over a wireless network. Wireless communication opens up the environment to huge vulnerabilities, making it very easy for hackers to gain access to sensitive information and carry out malicious actions. This paper proposes an M2M communication system through the internet in Tele-Robotics and provides network performance security. Tele-robotic systems are designed for surgery, treatment and diagnostics to be conducted across short or long distances while utilizing wireless communication networks. The systems also provide a low delay and secure communication system for the tele-robotics community and data security. The system can perform tasks autonomously and intelligently, minimizing the burden on medical staff and improving the quality and system performance of patient care. In the medical field, surgeons and patients are located at different places and connected through public networks. So the design of a medical sensor node network with LEACH protocol for secure and reliable communication ensures through the attack and without attack performance. Finally, the simulation results show low delay and reliable secure network transmission.

Quick & plenty: Achieving low delay & high rate in 802.11ac edge networks

We consider transport layer approaches for achieving high rate, low delay communication over edge paths where the bottleneck is an 802.11ac WLAN. We first show that by regulating send rate so as to maintain a target aggregation level it is possible to realise high rate, low delay communication over 802.11ac WLANs. We then address two important practical issues arising in production networks, namely that (i) many client devices are non-rooted mobile handsets/tablets and (ii) the bottleneck may lie in the backhaul rather than the WLAN, or indeed vary between the two over time. We show that both these issues can be resolved by use of simple and robust machine learning techniques. We present a prototype transport layer implementation of our low delay rate allocation approach and use this to evaluate performance under real radio conditions.

Average Secure BLER Analysis of NOMA Downlink Short-Packet Communication Systems in Flat Rayleigh Fading Channels

Incorporating short-packet communications with non-orthogonal multiple access (NOMA) networks is able to achieve both low communication delay and high spectral efficiency. In this article, a wireless NOMA downlink short-packet communication system is studied. The system includes a base station, an entrusted central user, and an untrusted cell-edge user. The untrusted cell-edge user may eavesdrop the signals from the base station to the central user. We theoretically derive the average secure block error rate (BLER) of the central user in flat Rayleigh fading channels by utilizing the linear approximations on BLER and secure BLER. We also present the asymptotic average secure BLER at high signal-to-noise ratio (SNR). From numerical results, it is shown that our derived analytical average secure BLER matches the simulated one. Numerical results also illustrate that at high SNR, error floors occur. Furthermore, at high SNR, it is found that when the average secure BLER is not one, the power allocation factors for the central and cell-edge users have almost no impact on the average secure BLER.

Toward Offloading Internet of Vehicles Applications in 5G Networks

The demand for real-time communication and high performance of the Internet of Vehicles (IoV) system has caused researches to investigate new techniques in edge computing (EC). With the rapid development of the fifth- generation (5G) network, the features of low delay, high reliability and superior communication efficiency can bring historic opportunities for the development of the EC-IoV system. In the 5G-enabled EC-IoV system, extreme densification of 5G base stations (gNBs) provides rapid and reliable network access and information interaction. However, this densification also brings more complex connectivity to the network, which increases the difficulty of resource migration and scheduling for the edge devices. Thus, it is still a challenge to manage the resources of the edge devices under the premise of reducing the energy and time cost in the system while avoiding the situation of overload or underload to maintain the stability of the system. In this article, a 5G-enabled EC-IoV system framework is proposed to enhance the performance of *the existing EC-IoV system. Specific computation offloading in 5G-enabled EC-IoV system is presented under three different cases. Through the above cases, two communication modes are concluded and the corresponding resource allocation strategy is given in this article. The performance of the proposed system is evaluated and compared with the existing system. Finally, future research directions in this area are considered.

Low-Complexity MIMO-FBMC Sparse Channel Parameter Estimation for Industrial Big Data Communications

Industrial applications can produce significant amounts of data that require low delay and high data rate communications. Multiple-input-multiple-output filter bank multicarrier (MIMO-FBMC) communications employing offset quadrature amplitude modulation has been proposed for industrial big data due to its reliability and high spectrum efficiency. One of the difficulties in implementing a MIMO-FBMC system is accurate channel estimation (CE). The main factor affecting the CE performance is intrinsic imaginary interference, and the conventional preamble-based CE is not effective in this case. Thus, in this article, a low-complexity sparse adaptive CE scheme is proposed that is based on a dynamic threshold. This reduces the number of inner product calculations by considering only the columns of the measurement matrix greater than the threshold. Simulation results are presented that show that the proposed scheme is better than other well-known methods in terms of computational complexity and CE accuracy.

Design and Development of Efficient Multipath TCP using GMM clustering for Big Data in Public Cloud Data Center

Currently new topologies have been introduced in many data centers that provide location independence and larger aggregate bandwidth by making different multiple paths in the network core. This work proposes transport of data from TCP (Transmission control Protocol) to multi-path TCP (MPTCP) for maximum utilization of paths over network flow. In spite of its added advantages, some sort of work on MPTCP to be carried out on cloud environment and further, efficient way of using MPTCP on real-world cloud application still looks like unclear problem. Further, the work also concerned on MPTCP usage in most effective and feasible way for cloud and data center environments over various conditions on network. The experiment is conducted by clustering the public cloud data using Gaussian Mixture Model (GMM) based Expectation and Maximization (EM) algorithm and communicated over a network using MPTCP. The results shows that the proposed method yields high-speed data transfer and low communication delay when compare to traditional TCP technique.

Design and Development of Efficient Multipath TCP for Data Center in Public Cloud

In recent days, variety of application development making use of cloud data centers effectively for analyzing data, processing related applications such as interactive and batch processing. Some of the factors influence on network performance by maintaining low delay, high-speed data transfer and more reliability. Maintaining and satisfying these factors becomes a challenging issue due to dynamic variations on network. TCP (Transmission control Protocol) proposed recently a new concept of multi-path TCP (MPTCP) for maximum utilization of paths over network flow. In spite of its added advantages, some sort of work on MPTCP to be carried out on cloud environment and further, efficient way of using MPTCP on real-world cloud application still looks like unclear problem. Our proposed work concerned on MPTCP usage in most effective and feasible way for cloud and data center environments over various conditions on network. The experiment is conducted by clustering the public cloud data using k-means algorithm and communicated over a network using MPTCP. The results shows that the proposed method yields high-speed data transfer and low communication delay when compare to traditional TCP technique.

An Extendable Layered Architecture for Collective Computing to Support Concurrent Multi-sourced Heterogeneous Tasks

Gregory D. Abowd shows a new vision of computer framework - collective computing. In this framework, kinds of remote computing devices, including even people who are regarded as a kind of computing device, are connected with each other into a group to complete a complex work. Therefore, the various computing devices with the different computing capacities can be fully used in different tasks. However, most of the relevant researches focus on improving infrastructure to address specific functions, the heterogeneous tasks performed in a common architecture and the large-scale integration are not paid enough attention. This paper presents a collective computing architecture for supporting concurrent multi-sourced heterogeneous tasks. The whole architecture is layered to provide different functions and obtain extensibility, loads balance, centralized dispatch and low delay communication. The extendible collective computing engine is used for analysing and allocating heterogeneous tasks, and the distributed device management controls heterogeneous computing devices. This architecture provides a common infrastructure for processing heterogeneous tasks by heterogeneous devices which dose not only design for some specialized systems or functions. At last, we implement a prototype system by this architecture for proving that the architecture can perform multi-sourced heterogeneous tasks well.

Enhanced Adaptive Cloudlet Placement Approach for Mobile Application on Spark

The applications of mobile devices are increasingly becoming computationally intensive while the computing capability of the user’s mobile device is limited. Traditional approaches offload the tasks of mobile applications to the remote cloud. However, the rapid growth of mobile devices has made it a challenge for the remote cloud to provide computing and storage capacities with low communication delays due to the fact that the remote cloud is geographically far away from mobile devices. Reducing the completion time of applications in mobile devices through the technical expending mobile cloudlets which are moving collocated with Access Points (APs) is necessary. To address the above issues, this paper proposes EACP-CA (Enhanced Adaptive Cloudlets Placement approach based on Covering Algorithm), an enhanced adaptive cloudlet placement approach for mobile applications in a given network area. We apply the CA (Covering Algorithm) to adaptively cluster the mobile devices based on their geographical locations, the aggregation regions of the mobile devices are identified, and the cloudlet destination locations are also confirmed according to the clustering centers. In addition, we can also obtain the traces between the original and destination locations of these mobile cloudlets. To increase the efficiency, we parallelize CA on Spark. Extensive experiments show that the proposed approach outperforms the existing approach in both effectiveness and efficiency.

Supporting Beacon and Event-Driven Messages in Vehicular Platoons through Token-Based Strategies.

Timely and reliable inter-vehicle communications is a critical requirement to support traffic safety applications, such as vehicle platooning. Furthermore, low-delay communications allow the platoon to react quickly to unexpected events. In this scope, having a predictable and highly effective medium access control (MAC) method is of utmost importance. However, the currently available IEEE 802.11p technology is unable to adequately address these challenges. In this paper, we propose a MAC method especially adapted to platoons, able to transmit beacons within the required time constraints, but with a higher reliability level than IEEE 802.11p, while concurrently enabling efficient dissemination of event-driven messages. The protocol circulates the token within the platoon not in a round-robin fashion, but based on beacon data age, i.e., the time that has passed since the previous collection of status information, thereby automatically offering repeated beacon transmission opportunities for increased reliability. In addition, we propose three different methods for supporting event-driven messages co-existing with beacons. Analysis and simulation results in single and multi-hop scenarios showed that, by providing non-competitive channel access and frequent retransmission opportunities, our protocol can offer beacon delivery within one beacon generation interval while fulfilling the requirements on low-delay dissemination of event-driven messages for traffic safety applications.

Guest Editorial

Guest Editorial

Video Metrics and Parameters for Achieving Optimal Quality in Low Delay Communication Networks

The need for optimal video quality over low delay communication networks is very crucial as their demand increases dramatically. Analysing, evaluating and exploring the codec metrics which can enhance the video quality when transporting the video over low delay communication networks has been a key issue of concern which requires thorough simulation and experimentation. Metrics such as quantization size, frame rate and frame size can significantly enhance the quality video. In this paper, the impacts of frame size, frame rate and quantization parameter on the compressed video quality has been investigated. More extensive simulations have been conducted in order to experiment different scenarios using various video samples at different frame sizes, quantization parameters, loss rate and encoding rate as well. More importantly, both low, medium and high complexity video samples have been examined to determine the impact of the aforementioned parameters on fundamental basic parameters which are essential toward yielding high-quality video while compressing videos. The experimental results show that increase in quantization parameter reduces the bits size and consequently leads to high compression.

An efficient EAP‐based proxy signature handover authentication scheme for WRANs over TV white space

SummaryThe wireless regional area networks (WRANs) operates in the very high frequency and ultra high frequency television white space bands regulated by the IEEE 802.22 standard. The IEEE 802.22 standard supports Extensible Authentication Protocol (EAP)‐based authentication scheme. Due to the participation of a server and the information exchanged between a customer primes equipment and the secondary user base station, it takes around 50 ms to complete a complete EAP authentication that cannot be accepted in a handover procedure in WRANs. In this paper, we propose an EAP‐based proxy signature (EPS) handover authentication scheme for WRANs. The customer primes equipment and secondary user base station accomplish a handover authentication without entailing the server by using the proxy signature. Approved by the logic derivation by Burrows, Abadi, and Needham logic and formal verification by Automated Validation of Internet Security Protocols and Applications, we can conclude that the proposed EPS scheme can obtain mutual authentication and hold the key secrecy with a strong antiattack ability. Additionally, the performance of the EPS scheme in terms of the authentication delay has been investigated by simulation experiments with the results showing that the EPS scheme is much more efficient in terms of low computation delay and less communication resources required than the security scheme regulated in IEEE 802.22 standard.

Decentralized Current Sharing Accuracy for Multi-terminal High Voltage DC System Based on Droop Control

In this article, a decentralized droop control scheme is proposed based on traditional current-voltage type droop control. This approach not only can eliminate the deviation of DC output voltage, it can also adjust the sharing accuracy of DC output current in multi-terminal high voltage DC systems. The averaging DC output voltage and current of two neighboring converters are employed to reduce the complexity of the communication networks, which include both radial and mesh configurations. In order to demonstrate the stability of the proposed method, the Pi-section line model of DC cable is used to simplify the model of multi-terminal high voltage DC networks, and the impact of varying DC cable impedance parameters and low bandwidth communication delay time are analyzed in detail. Finally, simulation results derived from a multi-terminal high voltage DC system is implemented in MATLAB/SIMULI-NK to verify the proposed approach.

Low-power neighbor discovery for mobility-aware wireless sensor networks

While more and more deployments of Wireless Sensor Networks (WSNs) are successful, very few are actually mobility-aware. Due to their intermittent connectivity, mobile nodes induce certain instabilities, and thus, require to transmit multiple data packets in a short period of time. The nature of mobile nodes can lead to a link quality deterioration or even more to link disconnection. This instability requires frequent link establishments between a mobile and a neighboring static node before initiating data packet transmissions. To do so, the need for an efficient Medium Access Control (MAC) protocol is extremely important and challenging. In this paper, we present MobiDisc, an advanced mobile-supporting scheme for low-power MAC protocols, which allows for efficient neighbor(hood) discovery and low-delay communication. Moreover, we propose a FAN (First Ack Next-hop) mode that accelerates transmissions. Both MobiDisc and MobiDisc-FAN come with a Fast Recovery Mechanism (FRM) that enables seamless handovers in the network. Our thorough performance evaluation, conducted on top of Contiki OS, shows that MobiDisc outperforms a number of state-of-the-art solutions (including MoX-MAC and ME-ContikiMAC), by terms of reducing both delay and energy consumption, while the reliability is kept over 98%.

IEEE 802.15.4 Beaconing Strategy and the Coexistence Problem in ISM Band

Over a home area network, between smart appliances and the smart meter, and over an 802.15.4g smart utility network, from a smart meter toward the utility center, IEEE 802.15.4 assists with advanced metering infrastructure components in a smart grid. Adopting the synchronous beacon-enabled mode of the IEEE 802.15.4 standard provides a slotted framework for low-power, real-time collection, and distribution of power information. However, the shared nature of the industrial, scientific, and medical (ISM) band introduces the beacon corruption issue, and confronts the 802.15.4-based network with service interruptions and large delays. This paper, experimentally and analytically, studies how interference from collocated networks affects the beaconing functionally and, consequently, network performance. Investigations indicate that beaconing contributes in low-power and low-delay communications over an 802.15.4 network only when its proper operation is guaranteed over a coexistent environment like ISM band; otherwise, the application delay is significantly compromised. In this regard, a standard-conforming enhancement, called the beacon corruption recovery scheme (BCRS), is proposed to mitigate effects of coexistence on beaconing performance by migration of the network to a cleaner channel. Simulation results show that by applying the BCRS, an 802.15.4 network experiences a less fragmented accesses to the medium and better fulfills real-time bidirectional flow of monitoring information.

AVS2 ? Making Video Coding Smarter [Standards in a Nutshell

AVS2 is a new generation of video coding standard developed by the IEEE 1857 Working Group under project 1857.4. AVS2 is also the second-generation video coding standard established by the Audio and Video Coding Standard (AVS) Working Group of China; the first-generation AVS1 was developed by the AVS Working Group and issued as Chinese national standard GB/T 20090.2-2006 in 2006. The AVS Working Group was founded in 2002 and is dedicated to providing the digital audio-video industry with highly efficient and economical coding/decoding technologies. So far, the AVS1 video coding standard is widely implemented in regional broadcasting, communication, and digital video entertainment systems. As the successor of AVS1, AVS2 is designed to achieve significant coding efficiency improvements relative to the preceding H.264/MPEG4-AVC and AVS1 standards. The basic coding framework of AVS2 is similar to the conterminous HEVC/H.265, but AVS2 can provide more efficient compression for certain video applications such as surveillance as well as low-delay communication such as videoconferencing. AVS2 is making video coding smarter by adopting intelligent coding tools that not only improve coding efficiency but also help with computer vision tasks such as object detection and tracking.

Distributed Source-Channel Coding Based on Real-Field BCH Codes

We use real-number codes to compress statistically dependent sources and establish a new framework for distributed lossy source coding in which we compress sources before, rather than after, quantization. This change in the order of binning and quantization blocks makes it possible to model the correlation between continuous-valued sources more realistically and compensate for the quantization error partially. We then focus on the asymmetric case, i.e., lossy source coding with side information at the decoder. The encoding and decoding procedures are described in detail for a class of real-number codes called discrete Fourier transform (DFT) codes, both for the syndrome- and parity-based approaches. We leverage subspace-based decoding to improve the decoding and by extending it we are able to perform distributed source coding in a rate-adaptive fashion to further improve the decoding performance when the statistical dependency between sources is unknown. We also extend the parity-based approach to the case where the transmission channel is noisy and thus we perform distributed joint source-channel coding in this context. The proposed system is well suited for low-delay communications, as the mean-squared reconstruction error (MSE) is shown to be reasonably low for very short block length.