High-bandwidth Services Research Articles

DenseNet-Transformer: A deep learning method for spatial–temporal traffic prediction in optical fronthaul network

The rapid evolution of 6G Radio Access Networks (RAN) towards virtualization and intelligence is driven by the widespread adoption of high-bandwidth services and the proliferation of mobile communications. Active Antenna Units (AAU) interface with Distributed Units (DU) over Passive Optical Networks (PON), serving as crucial bearers that transmit extensive data through the optical fronthaul network to the core network. However, the escalating demand for high-bandwidth services, coupled with the uneven spatial–temporal traffic patterns influenced by factors such as geographical location and urban functionalities across various base stations, poses significant challenges to the optical fronthaul network in terms of operational costs and resource allocation efficiency. To tackle these challenges, we introduce the DenseNet-Transformer spatial–temporal traffic prediction algorithm tailored specifically for the traffic characteristics of optical fronthaul networks. In DenseNet-Transformer, DenseNet captures spatial feature correlations among nearby traffic in adjacent regions, facilitating enhanced learning of traffic characteristics across distant areas through dense connections. The Transformer component learns both long and short-term temporal dependencies, enhancing the algorithm’s temporal prediction capabilities using multi-head attention mechanisms and positional encoding. We validate the effectiveness of DenseNet-Transformer through a series of ablation experiments and comparative tests against other algorithms under identical conditions. Experimental results on real datasets demonstrate that, in most scenarios, DenseNet-Transformer outperforms existing algorithms for time traffic prediction in both wireless and optical communication domains, as well as spatial–temporal prediction algorithms.

A Comprehensive Comparison of Simplified Volterra Equalization and Kramers–Kronig Schemes in 200 Gb/s/λ PON Downlink Transmission

The emerging high-bandwidth services of 6G, such as high-definition video transmission and real-time interaction, have promoted the progress of the fiber optic access network industry, driving its development towards the next-generation PON with higher speed and larger system capacity. In response to the future requirements of 200 Gb/s/λ PON for both 20 km and 30 km downlink transmission scenarios, this paper proposes a Simplified Volterra Equalization (SVLE) scheme based on Nyquist PAM4 single-sideband modulation direct detection (SSBM-DD) scheme. In order to verify its advantages, the IQ-modulated Kramers–Kronig reception (KK) scheme is introduced for comparison. Simulation validation platforms for two schemes are conducted, and the performance comparison of the SVLE and KK schemes is carried out. In both, the impact of the carrier signal power ratio (CSPR) on receiver sensitivity, the influence of input optical power on power budget and receiver sensitivity, and the tolerance of receiver sensitivity to the linewidth of the DFB laser are investigated in the simulation. Finally, a comprehensive comparison of the two schemes is presented in terms of system performance, cost, and DSP complexity. In the 20 km downlink transmission scenario, the SVLE scheme outperforms the KK scheme by 4.9 dB in terms of power budget. The total number of multiplications of the SVLE scheme is 37, while that of the KK scheme is 4358. Therefore, the DSP complexity of the SVLE scheme is much lower than that of the KK scheme. The results of the comparison demonstrate that, in downlink transmission scenarios, the SVLE scheme is more suitable than the KK scheme as it exhibits a higher power budget, lower DSP complexity, and lower cost. Consequently, the proposed SVLE scheme could be a highly promising solution for future ultra-high-speed PON downlink transmission.

Enabling seamless migration of optical metro-urban networks to the multi-band: unveiling a cutting-edge 6D planning tool for the 6G era

The relentless demand for high-bandwidth services and applications in the beyond-5G/6G era necessitates optical networks to provide ample spectral resources to accommodate the increasing traffic loads. This requirement is especially pronounced in metro and regional segments, where a projected traffic compound annual growth rate (CAGR) of over 40%, driven by content delivery network (CDN) traffic concentrated near the end users, threatens to push the fiber capacity to its limits on a number of heavily utilized links in the short to medium term. This limitation cannot be circumvented despite the utilization of spectrally efficient modulation formats designed for short-distance transmission. Thus, it is imperative to explore migration strategies to solutions that allow the expansion of spectral resources beyond the current usage of the extended C-band (4.8 THz). In this article, we present a comprehensive evaluation of multi-homed edge-to-core routing, modulation-level selection, and spectrum assignment simulations conducted over reference metropolitan area networks (MANs) by leveraging on a novel network planner called 6D-MAN, which we have developed to adapt to heterogeneous multi-layer networks based on multi-band and multi-fiber transmission. Our simulations consider coherent transmission with flexible modulation format transponders operating at capacities ranging from 100 to 400 Gbps on the 50 GHz grid and explore link-by-link migration strategies restricted to the C+L-band, ensuring optimal performance in terms of the generalized signal-to-noise ratio (GSNR). The obtained results demonstrate that deploying L-band equipment on a selected number of links effectively extends the lifespan of existing networks, enabling congestion-free operation with minimal intervention. In their entirety, our findings underscore the importance of contemplating alternative spectral resources beyond the conventional C-band. They unequivocally accentuate the potential of L-band equipment strategic deployment to tackle capacity constraints in MANs, resulting in a 60% reduction in fiber length and a remarkable 45% decrease in new fiber-pair link deployment needs. The profound implications of efficient fiber capacity utilization manifest themselves in substantial OPEX and optical total cost of ownership savings, amounting to approximately 71% and 17%–27%, respectively, over a 10-year period. This research provides valuable insights for MAN operators seeking sustainable strategies to support the growing demands of future beyond-5G/6G services.

Optimization Scheme of Trusted Task Offloading in IIoT Scenario Based爋n燚QN

With the development of the Industrial Internet of Things (IIoT), end devices (EDs) are equipped with more functions to capture information. Therefore, a large amount of data is generated at the edge of the network and needs to be processed. However, no matter whether these computing tasks are offloaded to traditional central clusters or mobile edge computing (MEC) devices, the data is short of security and may be changed during transmission. In view of this challenge, this paper proposes a trusted task offloading optimization scheme that can offer low latency and high bandwidth services for IIoT with data security. Blockchain technology is adopted to ensure data consistency. Meanwhile, to reduce the impact of low throughput of blockchain on task offloading performance, we design the processes of consensus and offloading as a Markov decision process (MDP) by defining states, actions, and rewards. Deep reinforcement learning (DRL) algorithm is introduced to dynamically select offloading actions. To accelerate the optimization, we design a novel reward function for the DRL algorithm according to the scale and computational complexity of the task. Experiments demonstrate that compared with methods without optimization, our mechanism performs better when it comes to the number of task offloading and throughput of blockchain.

Capacity and flexibility improvement of traffic aggregation for fixed 5G: Key enabling technologies, challenges and trends

As the emergence of various high-bandwidth services and the requirements to support 5G/Wi-Fi 6 wireless networks, the next generation fixed networks, i.e. F5G, are expected to be realized in the 5G era. F5G is endowed with new characteristics, including ultra-high bandwidth, all-optical connections and optimal service experience. With the prospect of optical-to-everywhere, optical technologies are used for mobile front-haul, mid-haul, and back-haul. Optical access networks would play an important role in F5G to support radio access network and fixed access network. Low-latency PON is a key for cost effective-haul traffic aggregation. In terms of signal transmission, intensity modulation direct-detection (IM-DD) is a promising scheme due to its simple architecture. The fundamental challenge associated with direct-detection is the disappearance of the transmitted signal's phase. In access network, the flexibility and low latency are the two key factors affecting service experience. In this article, we review the evolution of PONs and the challenges of current PONs in detail. We analyze key enabling digital signal processing (DSP) techniques, including detection linearization for direct-detection and simplified coherent detection, adaptive equalizers, digital filer enabled flexible access network and low-latency inter-ONU communications. Finally, we discuss the developing trends of future optical access networks.

Multi-band transparent optical network planning strategies for 6G-ready European networks

As long-haul network operators upgrade core optical networks to support 5G services, research and standardization efforts for 6G have begun. Keeping in mind the ever-growing demand for high-bandwidth services, our work proposes a novel core-network traffic model which exploits the network’s graph and population metric to estimate demands. We further develop a multi-period Routing, Configuration, and Spectrum Assignment (RCSA) algorithm which takes as input the traffic model demands, and provides network metrics spread across all planning periods.A multi-period multi-band transparent optical network planning study on three European networks is undertaken, using two deployment approaches; namely, flexible bandwidth variable transceivers (Flex-BVTs) and transparent IP over wavelength division multiplexing (IPoWDM). We show that Flex-BVT places up to 15% lesser equipment into the network while carrying up to 20% higher traffic. Using a simple Capital Expenditure (CAPEX) calculation, we also show that the CAPEX-per-bit of deploying Flex-BVTs is up to 12% lower, as compared to transparent IPoWDM solutions.

Socialized Learning for Smart Cities: Cognitive Paradigm, Methodology, and Solution

Along with the unprecedented boom of 5G, the Internet of Things (IoT), and artificial intelligence, smart cities are making a great clamor. When billions of IoT devices are streaming in the smart city, realizing low-latency and high-bandwidth services has a significant impact on the benefits of smart cities. Thus, managing resources efficiently and intelligently to meet various service requirements has become a challenge for smart cities. With the rapid development of machine intelligence, it can be considered that many machines constitute a machine society just like that of human beings. Inspired by the efficient and collaborative operation mechanism of human society, we propose a socialized learning scheme to address various needs in smart cities (e.g., reasonable resource allocation). Specifically, we present the socialized learning scheme from three perspectives. First, we design a cognitive paradigm of socialized learning to enlighten the long-term vision of applying learning-based resource management to smart cities, with comprehensive discussions of three dimensions consisting of architecture, decision, and knowledge. Second, we also probe the socialized learning methodology including socialized training and socialized inference. It highlights social relationships and introduces a series of technologies to realize social relations within and across layers. Finally, we give a socialized learning solution for solving the practical resource allocation problem in smart cities, thereby jointly improving decision accuracy and reducing training costs. Illustrative simulations are provided to show the effectiveness of the proposed scheme.

Virtual-Cache: A cache-line borrowing technique for efficient GPU cache architectures

GPUs provide megabytes of registers and shared memories to maintain the contexts for thousands of threads and enable fast data sharing amongst threads of a thread block, respectively. Besides, GPUs employ L1 cache to provide the high bandwidth service for memory requests. However, the average L1 cache capacity per thread is very limited, resulting in cache thrashing which in turn impairs the performance. Meanwhile, many registers and shared memories are unassigned to any warps or thread blocks. Moreover, registers and shared memories that are assigned can be idle when warps or thread blocks are finished. Exploiting the above insights, we propose Virtual-Cache to cost-effectively increase the effective size of L1 cache by utilizing the unassigned and released registers and shared memories as cache-lines in this paper. Specifically, we leverage the unassigned registers and shared memories to serve cache requests directly. Regarding the registers assigned to a warp, they can work as cache-lines after the warp completes the execution and before they are accessed again by a new launched warp. Regarding the shared memories of a thread block, they are enabled to serve cache requests when the thread block is finished till they are referenced by shared memory instructions of the relaunched thread block. The register file, shared memory and L1 cache are physically independent but logically unified as a large virtual cache with redesigned cache-line management. We develop the control and data path for the register file, making the register file accessible for cache requests by borrowing an operand collector to serve the cache requests. We also expand the control and data path for the shared memory to serve the cache requests. Our evaluation results show that Virtual-Cache makes the performance improved by 28% over the previously proposed cache management technique for cache-sensitive applications.

A Blockchain-Based Trusted Edge Platform in Edge Computing Environment.

Edge computing is a product of the evolution of IoT and the development of cloud computing technology, providing computing, storage, network, and other infrastructure close to users. Compared with the centralized deployment model of traditional cloud computing, edge computing solves the problems of extended communication time and high convergence traffic, providing better support for low latency and high bandwidth services. With the increasing amount of data generated by users and devices in IoT, security and privacy issues in the edge computing environment have become concerns. Blockchain, a security technology developed rapidly in recent years, has been adopted by many industries, such as finance and insurance. With the edge computing capability, deploying blockchain platforms/applications on edge computing platforms can provide security services for network edge environments. Although there are already solutions for integrating edge computing with blockchain in many IoT application scenarios, they slightly lack scalability, portability, and heterogeneous data processing. In this paper, we propose a trusted edge platform to integrate the edge computing framework and blockchain network for building an edge security environment. The proposed platform aims to preserve the data privacy of the edge computing client. The design based on the microservice architecture makes the platform lighter. To improve the portability of the platform, we introduce the Edgex Foundry framework and design an edge application module on the platform to improve the business capability of Edgex. Simultaneously, we designed a series of well-defined security authentication microservices. These microservices use the Hyperledger Fabric blockchain network to build a reliable security mechanism in the edge environment. Finally, we build an edge computing network using different hardware devices and deploy the trusted edge platform on multiple network nodes. The usability of the proposed platform is demonstrated by testing the round-trip time (RTT) of several important workflows. The experimental results demonstrate that the platform can meet the availability requirements in real-world usage scenarios.

Traffic Aggregation Based RSA (TARSA) for Time Varying Sub-Wavelength Connections in Elastic Optical Networks

Bandwidth in the spectrum sliced-elastic optical networks (EONs) can be allocated flexibly as per the users’ demand. Further, the allocated bandwidth on a connection can also be adjusted as per the traffic conditions and network scenarios. Currently, due to the growth in data centres, cloud computing based applications, and users’ tendency of using high bandwidth services, backbone network traffic has become more heterogeneous and time varying. This time varying and heterogeneous traffic in EONs is handled by the spectrum expansion/contraction (SEC) policies by adjusting the allocated spectrum as per the traffic requirement during network operation. In the SEC policies, the spectrum gap between anchor frequencies of two spectrum adjacent connections is shared to follow the traffic variations. The performance of the SEC policies depends on this spectral gap. This spectral gap is also termed as maximum allowable expansion region. Lower value of maximum allowable expansion region results in increased connection blocking and inefficient utilization of transmitter capacity. As a solution to these problems, we propose an efficient traffic aggregation based routing and spectrum allocation (TARSA) algorithm which increases the expansion region between the adjacent connections and improves the performance of the network. Performance evaluation of the proposed TARSA algorithm has been undertaken on the NSFNET and USNET network topologies on the metrics of average blocking rate and the percentage transmitters saving. It has been observed that the proposed TARSA improves the performance by reducing average blocking rate and by minimizing the number of transmitters used.

A Dual-Mode Medium Access Control Mechanism for UAV-Enabled Intelligent Transportation System

With the exponential growth in technologies for the vehicular Internet of things applications and high demands for autonomous road vehicles, future transportation systems are projected to be revolutionized on a global scale. This new landscape requires a stable, flexible, and business-friendly base of connectivity, networking, and computing technology, in which Unmanned Aerial Vehicles (UAVs) can play an important role. A UAV-enabled Intelligent Transportation System (ITS) can provide a cost-effective communication solution to improve the safety and efficiency of the transportation system, particularly if the data traffic is nonhomogeneous and nonstationary. Typically, wireless is the communication medium between vehicles and UAVs in an ITS setting, which is based on the IEEE802.11p MAC protocol adopted by car manufactures. However, the IEEE 802.11p MAC protocol is modified solely for omnidirectional antennas, which restricts network coverage, delay, and throughput. In comparison, the directional antenna has greater network coverage, spatial reuse, and bandwidth. In addition, a multiaccess edge computing (MEC) facility at the backhaul link will provide ultralow latency and high bandwidth services to meet the increasingly growing demand for latency-sensitive vehicle applications such as vehicular video data analytics, autonomous driving, and intelligent navigation. Therefore, this article aims to propose a novel dual-mode MAC protocol that can work in two antenna modes, i.e., directional and omnidirectional. For modeling and simulation purposes, we use the Optimized Network Engineering Tool (OPNET) and aim to seek an evaluation with respect to throughput, media access delay, and retransmission attempts. The results obtained demonstrate the effectiveness of the proposed scheme.

Determining of Optimal Telemedicine Communication Technologies with Regards to Network Interactive Modes: A Delphi Survey

Introduction: Different communication services with varying bandwidth are used to send information in the form of telemedicine technology. Bandwidth management, as defined in telemedicine technology, refers to using the desirable communication services according to the type of transaction and the information size to be transferred. Selection of communication services must be in such a way to result in minimum latency in the process of sending information and maintaining maximum cost-effectiveness.Material and Methods: This is an applied research which was conducted in 2019 by questionnaire survey amongst 60 participants, specialized in health information technology and medical informatics, who are working in hospitals and educational institutions of Tehran. Likert rating scale was used to quantify the research questions. Finally, by analyzing each weighted average, this study revealed the desirable communication services that correspond to the required transactions for deployment of telemedicine.Results: Transfer of multimedia information, using synchronized teleconferencing via primary low bandwidth technologies, had the lowest number average (0.96) and transmission of hybrid data (combination of picture, text, multimedia templates in synchronized or asynchronized modes) via Asymmetric Digital Subscriber Line (ADSL) technology had the highest average (4.96).Conclusion: Selection of communication services, with regard to its convergence with the information size and the type of their application, plays a significant role in controlling network traffic and preventing latency in the process of sending information in the context of telemedicine technology. High bandwidth communication services should be used for those telemedicine systems, which are offering services to many users, as well as those in which real-time transmission of information is essential. It needs to be pointed out that with regard to the cost-effectiveness of sending information, it is necessary to use low-cost services with low bandwidth for transfer of light weight information as well as for asynchronous applications in which latency in the process of information transfer is not detrimental.

Programmable Chip Based High Performance MEC Router for Ultra-Low Latency and High Bandwidth Services in Distributed Computing Environment

Programmable Chip Based High Performance MEC Router for Ultra-Low Latency and High Bandwidth Services in Distributed Computing Environment

Path Selection for Seamless Service Migration in Vehicular Edge Computing

Mobile-edge computing provisions computing and storage resources by deploying edge servers (ESs) at the edge of the network to support ultralow delay and high bandwidth services. To ensure QoS of latency-sensitive services in vehicular networks, service migration is required to migrate data of the ongoing services to the closest ES seamlessly when users move across different ESs. To achieve seamless service migration, path selection is proposed to obtain one or more paths (consisting of several switches and ESs) to transfer service data. We focus on the following problems about path selection: 1) where to implement path selection? 2) how to coordinate interests of mobile users (i.e., vehicles) and network providers since they have conflicting interests during path selection? and 3) how to ensure seamless service migration during the migration of vehicles? To address the above problems, this article investigates path selection for seamless service migration. We propose a path-selection algorithm to jointly optimize both interests of the network plane (i.e., the cost for network providers) and service plane (i.e., QoE of users). We first formulate it as a multiobjective optimization problem and further prove theoretically that the proposed algorithm can give a weakly Pareto-optimal solution . Moreover, to improve the scalability of the proposed algorithm, a distance-based filter strategy is designed to eliminate undesired switches in advance. We conduct experiments on two synthesized data sets and the results validate the effectiveness of the proposed algorithm.

Joint multi-dimensional resource allocation algorithm for a TWDM/OFDM-PON-based software-defined elastic optical access network

Abstract With the rapid growth of high-bandwidth services such as 5G, access networks only rely on physical layer technology to build a large-scale rigid pipeline, but cannot meet the need for the intelligent, flexible, and open networks of future business. Therefore, we herein propose a fairness-aware joint multi-dimensional resource allocation algorithm. It is based on software-defined elastic optical access network architecture and is intended to improve network throughput and the quality of service users experience. The simulation results show that the network throughput and user satisfaction rate of the proposed algorithm increases by about 30% during peak traffic periods compared with fixed allocation. The proposed algorithm can ensure that all users utilize the system bandwidth fairly.

Future edge clouds

Widespread deployment of centralized clouds has changed the way internet services are developed, deployed and operated. Centralized clouds have substantially extended the market opportunities for online services, enabled new entities to create and operate internet-scale services, and changed the way traditional companies run their operations. However, there are types of services that are unsuitable for today's centralized clouds such as highly interactive virtual and augmented reality (VR/AR) applications, high-resolution gaming, virtualized RAN, mass IoT data processing and industrial robot control. They can be broadly categorized as either latency-sensitive network functions, latency-sensitive applications, and/or high-bandwidth services. What these basic functions have in common is the need for a more distributed cloud infrastructure—an infrastructure we call edge clouds. In this paper, we examine the evolution of clouds, and edge clouds especially, and look at the developing market for edge clouds and what developments are required in networking, hardware and software to support them.

The Outlook for PON Standardization: A Tutorial

In light of the 5G deployments, edge computing, and future high bandwidth services, the industry is rethinking the optical access network architecture design. Passive optical network (PON) with its efficient fiber infrastructure plays an essential role in this design transformation. This article reviews the driving forces shaping the new generations of PON systems in the coming years; and discusses the course of action in the FSAN Group, ITU-T, and IEEE standards bodies to address the impending requirements.

Dynamic Resource Management of Real-Time Edge Services for Intelligent Vehicular Networks: A Case Study

The Internet of Vehicles requires high bandwidth and low latency services to unleash the potential of fully connected vehicles. Thus, the offloading proposals that successfully manage massive real-time service requests from vehicle nodes are needed. In this paper, we analyse the dynamic resource management for intelligent vehicular networks based on Multi-access Edge Computing architecture services. Using a combination of CloudSim and SUMO simulators, we present a case study of infotainment services in the city centre of Alicante, in Spain, that shows a high degree of optimality both in service allocation and migration when considering dense urban environments.

Performance of Bluetooth in Homogeneous Environment

Various wireless technologies use unlicensed ISM band in a frequency range 2.4GHz. Due to collocated, services causes mutual interference to one other; it degrades performance regarding Bit Error Rate (BER) and consequently throughput. The Bluetooth occupies less bandwidth and low power, gets more hampered as compare to other high bandwidth services is referred to as the heterogeneous environment. In this paper, an attempt is made to calculate the performance of basic rate Bluetooth in the presence of other Bluetooth devices in the close vicinity. The MATLAB based simulation results showed the degradation of performance of Bluetooth and enriched by selecting different hopping frequency in synchronisation with interfering Bluetooth devices.

Providing multicast services over SDN-evolved LTE network: Architecture, procedures and performance analysis

The recent innovation in cellular technologies like LTE/LTE-Advanced has increased the demand of high bandwidth services e.g. mobile Internet Protocol TV (IPTV), on-demand video streaming etc. However, current cellular multicast service called Evolved Multimedia Broadcast Multicast Service (eMBMS) is not enough in terms of IPTV service provisioning, flexibility, and efficiency. Software-defined networking (SDN) being an emerging networking paradigm offers its services to program such cellular networks, providing a remotely configurable forwarding plane. This paper enlightens the notion of SDN in cellular multicast data transmission within eMBMS networks. It presents an objective sketch of transforming current multicast cellular communication into OpenFlow based SDN-evolved communication. We perform the first fine-grained analysis of common multicast procedures (group join, handover etc.) involved in both the current and SDN-evolved eMBMS network along with the supporting simulation results while providing multimedia services to the users. Considering user plurality of multicast services, we model the user requests as independent events of a Zipf-like distribution and find out the correlation among multimedia content popularity, operational load on the network and delay metrics. This paper provides a comparison of both the networks, summarizes the significant differences between the two, and highlights the effectiveness of our proposed SDN-evolved multicast approach in terms of minimized network operations, reduced delays, reliable and streamlined multicast tree construction.