Cognitive optical network is the intermediate to combine artificial intelligence technology with network,and also the important network technology to promote network intelligence level constantly.In the paper,it analy...Cognitive optical network is the intermediate to combine artificial intelligence technology with network,and also the important network technology to promote network intelligence level constantly.In the paper,it analyzes the cognitive optical network structure with the application of artificial intelligence technology by starting from the basic conditions of cognitive network and cognitive optional network on the basis of fully understanding the connotation of cognitive network and cognitive optical network,and explores its self-governance functions,so as to better realize the self-optimization and self-configuration of network.展开更多
All optical network （AON） is a hot topic in recent studies of optical fiber communications. Key techniques in AON include optical switching/routing, optical cross connection （OXC）, all optical wavelength conversi...All optical network （AON） is a hot topic in recent studies of optical fiber communications. Key techniques in AON include optical switching/routing, optical cross connection （OXC）, all optical wavelength conversion （AOWC）, all optical buffering, etc. Opti- cal switching/routing is in fact wavelength switching/ routing. OXC and wavelength conversion （WC） are introduced into cross nodes so that a virtual wavelength path is established. With WC, communication route is formed only if there is unused wavelength in an individual segment link. The rate wavelength usage is thus greatly increased. The blocking rate of network can be reduced by adding WCs, especially for huge capacity multiple nodes ones. Therefore, WC has attracted much attention in basic research of optical communication and is used in some experimental networks.This dissertation studies all optic wavelength conversion and its application, with the contributions in the following five aspects.展开更多
As the types of traffic requests increase,the elastic optical network(EON)is considered as a promising architecture to carry multiple types of traffic requests simultaneously,including immediate reservation(IR)and adv...As the types of traffic requests increase,the elastic optical network(EON)is considered as a promising architecture to carry multiple types of traffic requests simultaneously,including immediate reservation(IR)and advance reservation(AR).Various resource allocation schemes for IR/AR requests have been designed in EON to reduce bandwidth blocking probability(BBP).However,these schemes do not consider different transmission requirements of IR requests and cannot maintain a low BBP for high-priority requests.In this paper,multi-priority is considered in the hybrid IR/AR request scenario.We modify the asynchronous advantage actor critic(A3C)model and propose an A3C-assisted priority resource allocation(APRA)algorithm.The APRA integrates priority and transmission quality of IR requests to design the A3C reward function,then dynamically allocates dedicated resources for different IR requests according to the time-varying requirements.By maximizing the reward,the transmission quality of IR requests can be matched with the priority,and lower BBP for high-priority IR requests can be ensured.Simulation results show that the APRA reduces the BBP of high-priority IR requests from 0.0341 to0.0138,and the overall network operation gain is improved by 883 compared to the scheme without considering the priority.展开更多
Optical network-on-chip(ONoC) systems have emerged as a promising solution to overcome limitations of traditional electronic interconnects. Efficient ONoC architectures rely on optical routers, enabling high-speed dat...Optical network-on-chip(ONoC) systems have emerged as a promising solution to overcome limitations of traditional electronic interconnects. Efficient ONoC architectures rely on optical routers, enabling high-speed data transfer, efficient routing, and scalability. This paper presents a comprehensive survey analyzing optical router designs, specifically microring resonators(MRRs), Mach-Zehnder interferometers(MZIs), and hybrid architectures. Selected comparison criteria, chosen for their critical importance, significantly impact router functionality and performance. By emphasizing these criteria, valuable insights into the strengths and limitations of different designs are gained, facilitating informed decisions and advancements in optical networking. While other factors contribute to performance and efficiency, the chosen criteria consistently address fundamental elements, enabling meaningful evaluation. This work serves as a valuable resource for beginners, providing a solid foundation in understanding ONoC and optical routers. It also offers an in-depth survey for experts, laying the groundwork for further exploration. Additionally, the importance of considering design constraints and requirements when selecting an optimal router design is highlighted. Continued research and innovation will enable the development of efficient optical router solutions that meet the evolving needs of modern computing systems. This survey underscores the significance of ongoing advancements in the field and their potential impact on future technologies.展开更多
Multi-band optical networks are a potential technology for increasing network capacity.However,the strong interference and non-uniformity between wavelengths in multi-band optical networks have become a bottleneck res...Multi-band optical networks are a potential technology for increasing network capacity.However,the strong interference and non-uniformity between wavelengths in multi-band optical networks have become a bottleneck restricting the transmission capacity of multi-band optical networks.To overcome these challenges,it is particularly important to implement optical power optimization targeting wavelength differences.Therefore,based on the generalized Gaussian noise model,we first formulate an optimization model for the problems of routing,modulation format,wavelength,and power allocation in C+L+S multi-band optical networks.Our objective function is to maximize the average link capacity of the network while ensuring that the Optical Signal-to-Noise(OSNR)threshold of the service request is not exceeded.Next,we propose a NonLinear Interferenceaware(NLI-aware)routing,modulation format,wavelength,and power allocation algorithm.Finally,we conduct simulations under different test conditions.The simulation results indicate that our algorithm can effectively reduce the blocking probability by 23.5%and improve the average link capacity by 3.78%in C+L+S multi-band optical networks.展开更多
In the context of the rapid iteration of information technology,the Internet of Things(IoT)has established itself as a pivotal hub connecting the digital world and the physical world.Wireless Sensor Networks(WSNs),dee...In the context of the rapid iteration of information technology,the Internet of Things(IoT)has established itself as a pivotal hub connecting the digital world and the physical world.Wireless Sensor Networks(WSNs),deeply embedded in the perception layer architecture of the IoT,play a crucial role as“tactile nerve endings.”A vast number of micro sensor nodes are widely distributed in monitoring areas according to preset deployment strategies,continuously and accurately perceiving and collecting real-time data on environmental parameters such as temperature,humidity,light intensity,air pressure,and pollutant concentration.These data are transmitted to the IoT cloud platform through stable and reliable communication links,forming a massive and detailed basic data resource pool.By using cutting-edge big data processing algorithms,machine learning models,and artificial intelligence analysis tools,in-depth mining and intelligent analysis of these multi-source heterogeneous data are conducted to generate high-value-added decision-making bases.This precisely empowers multiple fields,including agriculture,medical and health care,smart home,environmental science,and industrial manufacturing,driving intelligent transformation and catalyzing society to move towards a new stage of high-quality development.This paper comprehensively analyzes the technical cores of the IoT and WSNs,systematically sorts out the advanced key technologies of WSNs and the evolution of their strategic significance in the IoT system,deeply explores the innovative application scenarios and practical effects of the two in specific vertical fields,and looks forward to the technological evolution trends.It provides a detailed and highly practical guiding reference for researchers,technical engineers,and industrial decision-makers.展开更多
Propelled by the rise of artificial intelligence,cloud services,and data center applications,next-generation,low-power,local-oscillator-less,digital signal processing(DSP)-free,and short-reach coherent optical communi...Propelled by the rise of artificial intelligence,cloud services,and data center applications,next-generation,low-power,local-oscillator-less,digital signal processing(DSP)-free,and short-reach coherent optical communication has evolved into an increasingly prominent area of research in recent years.Here,we demonstrate DSP-free coherent optical transmission by analog signal processing in frequency synchronous optical network(FSON)architecture,which supports polarization multiplexing and higher-order modulation formats.The FSON architecture that allows the numerous laser sources of optical transceivers within a data center can be quasi-synchronized by means of a tree-distributed homology architecture.In conjunction with our proposed pilot-tone assisted Costas loop for an analog coherent receiver,we achieve a record dual-polarization 224-Gb/s 16-QAM 5-km mismatch transmission with reset-free carrier phase recovery in the optical domain.Our proposed DSP-free analog coherent detection system based on the FSON makes it a promising solution for next-generation,low-power,and high-capacity coherent data center interconnects.展开更多
This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocatio...This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocation (RSA). The proposed method, Dynamic Threshold-Based Routing and Spectrum Allocation with Fragmentation Awareness (DT-RSAF), integrates rerouting and spectrum defragmentation as needed. By leveraging Yen’s shortest path algorithm, DT-RSAF enhances resource utilization while ensuring improved service continuity. A dynamic threshold mechanism enables the algorithm to adapt to varying network conditions, while its fragmentation awareness effectively mitigates spectrum fragmentation. Simulation results on NSFNET and COST 239 topologies demonstrate that DT-RSAF significantly outperforms methods such as K-Shortest Path Routing and Spectrum Allocation (KSP-RSA), Load Balanced and Fragmentation-Aware (LBFA), and the Invasive Weed Optimization-based RSA (IWO-RSA). Under heavy traffic, DT-RSAF reduces the blocking probability by up to 15% and achieves lower Bandwidth Fragmentation Ratios (BFR), ranging from 74% to 75%, compared to 77% - 80% for KSP-RSA, 75% - 77% for LBFA, and approximately 76% for IWO-RSA. DT-RSAF also demonstrated reasonable computation times compared to KSP-RSA, LBFA, and IWO-RSA. On a small-sized network, its computation time was 8710 times faster than that of Integer Linear Programming (ILP) on the same network topology. Additionally, it achieved a similar execution time to LBFA and outperformed IWO-RSA in terms of efficiency. These results highlight DT-RSAF’s capability to maintain large contiguous frequency blocks, making it highly effective for accommodating high-bandwidth requests in EONs while maintaining reasonable execution times.展开更多
Reconfigurable linear optical networks based on Mach-Zehnder interferometer(MZI)offer significant potential in optical information processing,particularly in emerging photonic quantum computing systems.However,device ...Reconfigurable linear optical networks based on Mach-Zehnder interferometer(MZI)offer significant potential in optical information processing,particularly in emerging photonic quantum computing systems.However,device losses and calibration errors accumulate as network complexity grows,posing challenges in performing precise mapping of matrix operations.Existing architectures,such as Diamond and Bokun,introduce MZI redundancy into Reck and Clements architectures to improve reliability,which increases complexity and differential path losses that limit scalability.We propose a compact topology architecture that achieves 100%fidelity by employing a symmetrical MZI to decouple optical loss from power ratio and introducing extra MZIs to enforce uniform loss distributions.This multi-level optimization enables direct monitoring pathways while supporting precise calibration,and it approaches theoretical fidelity in practical deployments with direct implications for scalable and fault-tolerant photonic computing systems.展开更多
The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vi...The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vision,Federated Learning(FL)has gained prominence as a distributed machine learning framework that allows multiple devices to collaboratively train models without sharing raw data,thereby preserving privacy and reducing the need for centralized storage.This capability is particularly attractive for vision-based applications,where image and video data are both sensitive and bandwidth-intensive.However,the integration of FL with 6G networks presents unique challenges,including communication bottlenecks,device heterogeneity,and trade-offs between model accuracy,latency,and energy consumption.In this paper,we developed a simulation-based framework to investigate the performance of FL in representative vision tasks under 6G-like environments.We formalize the system model,incorporating both the federated averaging(FedAvg)training process and a simplified communication costmodel that captures bandwidth constraints,packet loss,and variable latency across edge devices.Using standard image datasets(e.g.,MNIST,CIFAR-10)as benchmarks,we analyze how factors such as the number of participating clients,degree of data heterogeneity,and communication frequency influence convergence speed and model accuracy.Additionally,we evaluate the effectiveness of lightweight communication-efficient strategies,including local update tuning and gradient compression,in mitigating network overhead.The experimental results reveal several key insights:(i)communication limitations can significantly degrade FL convergence in vision tasks if not properly addressed;(ii)judicious tuning of local training epochs and client participation levels enables notable improvements in both efficiency and accuracy;and(iii)communication-efficient FL strategies provide a promising pathway to balance performance with the stringent latency and reliability requirements expected in 6G.These findings highlight the synergistic role of AI and nextgeneration networks in enabling privacy-preserving,real-time vision applications,and they provide concrete design guidelines for researchers and practitioners working at the intersection of FL and 6G.展开更多
Quantum key distribution(QKD)optical networks can provide more secure communications.However,with the increase of the QKD path requests and key updates,network blocking problems will become severe.The blocking problem...Quantum key distribution(QKD)optical networks can provide more secure communications.However,with the increase of the QKD path requests and key updates,network blocking problems will become severe.The blocking problems in the network can become more severe because each fiber link has limited resources(such as wavelengths and time slots).In addition,QKD optical networks are also affected by external disturbances such as data interception and eavesdropping,resulting in inefficient network communication.In this paper,we exploit the idea of protection path to enhance the anti-interference ability of QKD optical network.By introducing the concept of security metric,we propose a routing wavelength and time slot allocation algorithm(RWTA)based on protection path,which can lessen the blocking problem of QKD optical network.According to simulation analysis,the security-metric-based RWTA algorithm(SM-RWTA)proposed in this paper can substantially improve the success rate of security key(SK)update and significantly reduce the blocking rate of the network.It can also improve the utilization rate of resources such as wavelengths and time slots.Compared with the non-security-metric-based RWTA algorithm(NSM-RWTA),our algorithm is robust and can enhance the anti-interference ability and security of QKD optical networks.展开更多
Due to the increasing variety of information and services carried by optical networks, the survivability of network becomes an important problem in current research. The fault location of OTN is of great significance ...Due to the increasing variety of information and services carried by optical networks, the survivability of network becomes an important problem in current research. The fault location of OTN is of great significance for studying the survivability of optical networks. Firstly, a three-channel network model is established and analyzing common alarm data, the fault monitoring points and common fault points are carried out. The artificial neural network is introduced into the fault location field of OTN and it is used to judge whether the possible fault point exists or not. But one of the obvious limitations of general neural networks is that they receive a fixedsize vector as input and produce a fixed-size vector as the output. Not only that, these models is even fixed for mapping operations (for example, the number of layers in the model). The difference between the recurrent neural network and general neural networks is that it can operate on the sequence. In spite of the fact that the gradient disappears and the gradient explodes still exist in the neural network, the method of gradient shearing or weight regularization is adopted to solve this problem, and choose the LSTM (long-short term memory networks) to locate the fault. The output uses the concept of membership degree of fuzzy theory to express the possible fault point with the probability from 0 to 1. Priority is given to the treatment of fault points with high probability. The concept of F-Measure is also introduced, and the positioning effect is measured by using location time, MSE and F-Measure. The experiment shows that both LSTM and BP neural network can locate the fault of optical transport network well, but the overall effect of LSTM is better. The localization time of LSTM is shorter than that of BP neural network, and the F1-score of LSTM can reach 0.961566888396156 after 45 iterations, which meets the accuracy and real-time requirements of fault location. Therefore, it has good application prospect and practical value to introduce neural network into the fault location field of optical transport network.展开更多
AIM: To explore a segmentation algorithm based on deep learning to achieve accurate diagnosis and treatment of patients with retinal fluid.METHODS: A two-dimensional(2D) fully convolutional network for retinal segment...AIM: To explore a segmentation algorithm based on deep learning to achieve accurate diagnosis and treatment of patients with retinal fluid.METHODS: A two-dimensional(2D) fully convolutional network for retinal segmentation was employed. In order to solve the category imbalance in retinal optical coherence tomography(OCT) images, the network parameters and loss function based on the 2D fully convolutional network were modified. For this network, the correlations of corresponding positions among adjacent images in space are ignored. Thus, we proposed a three-dimensional(3D) fully convolutional network for segmentation in the retinal OCT images.RESULTS: The algorithm was evaluated according to segmentation accuracy, Kappa coefficient, and F1 score. For the 3D fully convolutional network proposed in this paper, the overall segmentation accuracy rate is 99.56%, Kappa coefficient is 98.47%, and F1 score of retinal fluid is 95.50%. CONCLUSION: The OCT image segmentation algorithm based on deep learning is primarily founded on the 2D convolutional network. The 3D network architecture proposed in this paper reduces the influence of category imbalance, realizes end-to-end segmentation of volume images, and achieves optimal segmentation results. The segmentation maps are practically the same as the manual annotations of doctors, and can provide doctors with more accurate diagnostic data.展开更多
An optical network is a type of data communication network built with optical fibre technology. It utilizes optical fibre cables as the primary communication medium for converting data and passing data as light pulses...An optical network is a type of data communication network built with optical fibre technology. It utilizes optical fibre cables as the primary communication medium for converting data and passing data as light pulses between sender and receiver nodes. The major issue in optical networking is disjoints that occur in the network. A polynomial time algorithm Wavelength Division Multiplexing-Passive Optical Networking (WDM-PON) computes disjoints of an optical network and reduces the count of disjoints that occur in the network by separating Optical Network Units (ONU) into several virtual point-to-point connections. The Arrayed Waveguide Grating (AWG) filter is included in WDM-PON to avoid the traffic in the network thereby increasing the bandwidth capacity. In case of a failure or disjoint Ant Colony Optimization (ACO) algorithm is used to find the optimized shortest path for re-routing. For enhanced security, modified Rivert Shamir Adleman (RSA) algorithm encrypts the message during communication between the nodes. The efficiency is found to be improved in terms of delay in packet delivery, longer optical reach, optimized shortest path, packet error rate.展开更多
With the capacities of self-learning,acquainted capacities,high-speed looking for ideal arrangements,solid nonlin-ear fitting,and mapping self-assertively complex nonlinear relations,neural systems have made incredibl...With the capacities of self-learning,acquainted capacities,high-speed looking for ideal arrangements,solid nonlin-ear fitting,and mapping self-assertively complex nonlinear relations,neural systems have made incredible advances and accomplished broad application over the final half-century.As one of the foremost conspicuous methods for fake insights,neural systems are growing toward high computational speed and moo control utilization.Due to the inborn impediments of electronic gadgets,it may be troublesome for electronic-implemented neural systems to make the strides these two exhibitions encourage.Optical neural systems can combine optoelectronic procedures and neural organization models to provide ways to break the bottleneck.This paper outlines optical neural networks of feedforward repetitive and spiking models to give a clearer picture of history,wildernesses,and future optical neural systems.The framework demonstrates neural systems in optic communication with the serial and parallel setup.The graphene-based laser structure for fiber optic communication is discussed.The comparison of different balance plans for photonic neural systems is made within the setting of hereditary calculation and molecule swarm optimization.In expansion,the execution comparison of routine photonic neural,time-domain with and without extending commotion is additionally expounded.The challenges and future patterns of optical neural systems on the growing scale and applications of in situ preparing nonlinear computing will hence be uncovered.展开更多
An Extrinsic Fabry-Perot Interferometric (EFPI) fiber optical sensor system is an online testing system for the gas density. The system achieves the measurement of gas density information mainly by demodulating the ca...An Extrinsic Fabry-Perot Interferometric (EFPI) fiber optical sensor system is an online testing system for the gas density. The system achieves the measurement of gas density information mainly by demodulating the cavity length of EF- PI fiber optical sensor. There are many ways to achieve the demodulation of the cavity length. For shortcomings of the big intensity demodulation error and complex structure of phase demodulation, this paper proposes that BP neural net-work is used to locate the special peak points in normalized interference spectrum and combining the advantages of the unimodal and bimodal measurement achieves the demodulation of the cavity length. Through online simulation and actual measurement, the results show that the peak positioning technology based on BP neural network can not only achieve high-precision demodulation of the cavity length, but also achieve an absolute measurement of cavity length in large dynamic range.展开更多
One fiber radio scheme using shifted prime codes for interference elimination is proposed for optical code-division multiple-access (OCDMA) network. By taking advantage of the cyclic property of the shifted prime code...One fiber radio scheme using shifted prime codes for interference elimination is proposed for optical code-division multiple-access (OCDMA) network. By taking advantage of the cyclic property of the shifted prime codes in the same code groups, the proposed compact decoder is low cost and suitable to be used in the task manager node in the applications of wireless sensor networks. The performance comparison for sev-eral OCDMA-based fiber radio networks is also given to clarify the advantage of the proposed one.展开更多
Network virtualization is important for elastic optical networks(EONs)because of more flexible service provisioning.To ensure guaranteed quality of service(QoS)for each virtual elastic optical network(VEON),clients us...Network virtualization is important for elastic optical networks(EONs)because of more flexible service provisioning.To ensure guaranteed quality of service(QoS)for each virtual elastic optical network(VEON),clients usually request network resources from a network operator based on their bandwidth requirements predicted from historical traffic demands.However,this may not be efficient as the actual traffic demands of users always fluctuate.To tackle this,we propose a new VEON service provisioning scheme,called SATP,which consists of three stages,i.e.,spectrum assignment(SA),spectrum trading(ST),and spectrum purchasing(SP).Unlike conventional once-for-all VEON service provisioning approaches,the SATP scheme first allocates spectrum resources to VEONs according to their predicted bandwidth requirements with a satisfaction ratio α(0<α≤1).Then,to minimize service degradation on VEONs which are short of assigned spectra for their peak traffic periods,the scheme allows VEONs to trade spectra with each other according to their actual bandwidth requirements.Finally,it allows VEON clients to purchase extra spectrum resources from a network operator if the spectrum resources are still insufficient.To optimize this entire process,we formulate the problem as a mixed integer linear programming(MILP)model and also develop efficient heuristic algorithms for each stage to handle large test scenarios.Simulations are conducted under different test conditions for both static and dynamic traffic demand scenarios.Results show that the proposed SATP scheme is efficient and can achieve significant performance improvement under both static and dynamic scenarios.展开更多
A passive optical network （PON） scheme based on optical code division multiplexing （OCDM） for the downstream traffics is proposed and analyzed in detail. In the PON, the downstream traffics are broadcasted by OCDM...A passive optical network （PON） scheme based on optical code division multiplexing （OCDM） for the downstream traffics is proposed and analyzed in detail. In the PON, the downstream traffics are broadcasted by OCDM technology to guarantee the security, while the upstream traffics pass through the same optical fiber by the common time division multiple access （TDMA） technology to decrease the cost. This schemes are denoted as OCDM/TDMA-PON, which can be applied to an optical access network （OAN） with full services on demand, such as Internet protocol, video on demand, tele-presence and high quality audio. The proposed OCDM/TDMA-PON scheme combines advantages of PON, TDMA, and OCDM technology. Simulation results indicate that the designed scheme improves the OAN performance, and enhances flexibility and scalability of the system.展开更多
As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model...As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model that makes full use of the gate recurrent unit(GRU)algorithm.Based on the fragmentation prediction model,one virtual optical network mapping scheme is presented for edge computing driven EON.With the minimum of fragmentation degree all over the whole EON,the virtual network mapping can be successively conducted.Test results show that the proposed approach can reduce blocking rate,and the supporting ability for virtual optical network services is greatly improved.展开更多
文摘Cognitive optical network is the intermediate to combine artificial intelligence technology with network,and also the important network technology to promote network intelligence level constantly.In the paper,it analyzes the cognitive optical network structure with the application of artificial intelligence technology by starting from the basic conditions of cognitive network and cognitive optional network on the basis of fully understanding the connotation of cognitive network and cognitive optical network,and explores its self-governance functions,so as to better realize the self-optimization and self-configuration of network.
文摘All optical network （AON） is a hot topic in recent studies of optical fiber communications. Key techniques in AON include optical switching/routing, optical cross connection （OXC）, all optical wavelength conversion （AOWC）, all optical buffering, etc. Opti- cal switching/routing is in fact wavelength switching/ routing. OXC and wavelength conversion （WC） are introduced into cross nodes so that a virtual wavelength path is established. With WC, communication route is formed only if there is unused wavelength in an individual segment link. The rate wavelength usage is thus greatly increased. The blocking rate of network can be reduced by adding WCs, especially for huge capacity multiple nodes ones. Therefore, WC has attracted much attention in basic research of optical communication and is used in some experimental networks.This dissertation studies all optic wavelength conversion and its application, with the contributions in the following five aspects.
文摘As the types of traffic requests increase,the elastic optical network(EON)is considered as a promising architecture to carry multiple types of traffic requests simultaneously,including immediate reservation(IR)and advance reservation(AR).Various resource allocation schemes for IR/AR requests have been designed in EON to reduce bandwidth blocking probability(BBP).However,these schemes do not consider different transmission requirements of IR requests and cannot maintain a low BBP for high-priority requests.In this paper,multi-priority is considered in the hybrid IR/AR request scenario.We modify the asynchronous advantage actor critic(A3C)model and propose an A3C-assisted priority resource allocation(APRA)algorithm.The APRA integrates priority and transmission quality of IR requests to design the A3C reward function,then dynamically allocates dedicated resources for different IR requests according to the time-varying requirements.By maximizing the reward,the transmission quality of IR requests can be matched with the priority,and lower BBP for high-priority IR requests can be ensured.Simulation results show that the APRA reduces the BBP of high-priority IR requests from 0.0341 to0.0138,and the overall network operation gain is improved by 883 compared to the scheme without considering the priority.
文摘Optical network-on-chip(ONoC) systems have emerged as a promising solution to overcome limitations of traditional electronic interconnects. Efficient ONoC architectures rely on optical routers, enabling high-speed data transfer, efficient routing, and scalability. This paper presents a comprehensive survey analyzing optical router designs, specifically microring resonators(MRRs), Mach-Zehnder interferometers(MZIs), and hybrid architectures. Selected comparison criteria, chosen for their critical importance, significantly impact router functionality and performance. By emphasizing these criteria, valuable insights into the strengths and limitations of different designs are gained, facilitating informed decisions and advancements in optical networking. While other factors contribute to performance and efficiency, the chosen criteria consistently address fundamental elements, enabling meaningful evaluation. This work serves as a valuable resource for beginners, providing a solid foundation in understanding ONoC and optical routers. It also offers an in-depth survey for experts, laying the groundwork for further exploration. Additionally, the importance of considering design constraints and requirements when selecting an optimal router design is highlighted. Continued research and innovation will enable the development of efficient optical router solutions that meet the evolving needs of modern computing systems. This survey underscores the significance of ongoing advancements in the field and their potential impact on future technologies.
基金supported in part by the National Natural Science Foundation of China under Grants U21B2005,62201105,62331017,U24B20134,62222103,and 62025105in part by the Chongqing Municipal Education Commission under Grants KJQN202400621,KJQN202100643,and KJZDK202400608+1 种基金in part by the China Postdoctoral Science Foundation under Grant 2021M700563in part by the Chongqing Postdoctoral Funding Project under Grant 2021XM3052。
文摘Multi-band optical networks are a potential technology for increasing network capacity.However,the strong interference and non-uniformity between wavelengths in multi-band optical networks have become a bottleneck restricting the transmission capacity of multi-band optical networks.To overcome these challenges,it is particularly important to implement optical power optimization targeting wavelength differences.Therefore,based on the generalized Gaussian noise model,we first formulate an optimization model for the problems of routing,modulation format,wavelength,and power allocation in C+L+S multi-band optical networks.Our objective function is to maximize the average link capacity of the network while ensuring that the Optical Signal-to-Noise(OSNR)threshold of the service request is not exceeded.Next,we propose a NonLinear Interferenceaware(NLI-aware)routing,modulation format,wavelength,and power allocation algorithm.Finally,we conduct simulations under different test conditions.The simulation results indicate that our algorithm can effectively reduce the blocking probability by 23.5%and improve the average link capacity by 3.78%in C+L+S multi-band optical networks.
文摘In the context of the rapid iteration of information technology,the Internet of Things(IoT)has established itself as a pivotal hub connecting the digital world and the physical world.Wireless Sensor Networks(WSNs),deeply embedded in the perception layer architecture of the IoT,play a crucial role as“tactile nerve endings.”A vast number of micro sensor nodes are widely distributed in monitoring areas according to preset deployment strategies,continuously and accurately perceiving and collecting real-time data on environmental parameters such as temperature,humidity,light intensity,air pressure,and pollutant concentration.These data are transmitted to the IoT cloud platform through stable and reliable communication links,forming a massive and detailed basic data resource pool.By using cutting-edge big data processing algorithms,machine learning models,and artificial intelligence analysis tools,in-depth mining and intelligent analysis of these multi-source heterogeneous data are conducted to generate high-value-added decision-making bases.This precisely empowers multiple fields,including agriculture,medical and health care,smart home,environmental science,and industrial manufacturing,driving intelligent transformation and catalyzing society to move towards a new stage of high-quality development.This paper comprehensively analyzes the technical cores of the IoT and WSNs,systematically sorts out the advanced key technologies of WSNs and the evolution of their strategic significance in the IoT system,deeply explores the innovative application scenarios and practical effects of the two in specific vertical fields,and looks forward to the technological evolution trends.It provides a detailed and highly practical guiding reference for researchers,technical engineers,and industrial decision-makers.
基金supported by the National Natural Science Foundation of China(Grant Nos.62405250 and 62471404)the China Postdoctoral Science Foundation(Grant No.2024M762955)+1 种基金the Key Project of Westlake Institute for Optoelectronics(Grant No.2023GD003)the Optical Com-munication and Sensing Laboratory,School of Engineering,Westlake University.
文摘Propelled by the rise of artificial intelligence,cloud services,and data center applications,next-generation,low-power,local-oscillator-less,digital signal processing(DSP)-free,and short-reach coherent optical communication has evolved into an increasingly prominent area of research in recent years.Here,we demonstrate DSP-free coherent optical transmission by analog signal processing in frequency synchronous optical network(FSON)architecture,which supports polarization multiplexing and higher-order modulation formats.The FSON architecture that allows the numerous laser sources of optical transceivers within a data center can be quasi-synchronized by means of a tree-distributed homology architecture.In conjunction with our proposed pilot-tone assisted Costas loop for an analog coherent receiver,we achieve a record dual-polarization 224-Gb/s 16-QAM 5-km mismatch transmission with reset-free carrier phase recovery in the optical domain.Our proposed DSP-free analog coherent detection system based on the FSON makes it a promising solution for next-generation,low-power,and high-capacity coherent data center interconnects.
文摘This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocation (RSA). The proposed method, Dynamic Threshold-Based Routing and Spectrum Allocation with Fragmentation Awareness (DT-RSAF), integrates rerouting and spectrum defragmentation as needed. By leveraging Yen’s shortest path algorithm, DT-RSAF enhances resource utilization while ensuring improved service continuity. A dynamic threshold mechanism enables the algorithm to adapt to varying network conditions, while its fragmentation awareness effectively mitigates spectrum fragmentation. Simulation results on NSFNET and COST 239 topologies demonstrate that DT-RSAF significantly outperforms methods such as K-Shortest Path Routing and Spectrum Allocation (KSP-RSA), Load Balanced and Fragmentation-Aware (LBFA), and the Invasive Weed Optimization-based RSA (IWO-RSA). Under heavy traffic, DT-RSAF reduces the blocking probability by up to 15% and achieves lower Bandwidth Fragmentation Ratios (BFR), ranging from 74% to 75%, compared to 77% - 80% for KSP-RSA, 75% - 77% for LBFA, and approximately 76% for IWO-RSA. DT-RSAF also demonstrated reasonable computation times compared to KSP-RSA, LBFA, and IWO-RSA. On a small-sized network, its computation time was 8710 times faster than that of Integer Linear Programming (ILP) on the same network topology. Additionally, it achieved a similar execution time to LBFA and outperformed IWO-RSA in terms of efficiency. These results highlight DT-RSAF’s capability to maintain large contiguous frequency blocks, making it highly effective for accommodating high-bandwidth requests in EONs while maintaining reasonable execution times.
基金supported by the Innovation Program for Quantum Science and Technology(Grant Nos.2021ZD0301400 and 2023ZD0301500)the National Natural Science Foundation of China(Grant Nos.62335019 and 62475291).
文摘Reconfigurable linear optical networks based on Mach-Zehnder interferometer(MZI)offer significant potential in optical information processing,particularly in emerging photonic quantum computing systems.However,device losses and calibration errors accumulate as network complexity grows,posing challenges in performing precise mapping of matrix operations.Existing architectures,such as Diamond and Bokun,introduce MZI redundancy into Reck and Clements architectures to improve reliability,which increases complexity and differential path losses that limit scalability.We propose a compact topology architecture that achieves 100%fidelity by employing a symmetrical MZI to decouple optical loss from power ratio and introducing extra MZIs to enforce uniform loss distributions.This multi-level optimization enables direct monitoring pathways while supporting precise calibration,and it approaches theoretical fidelity in practical deployments with direct implications for scalable and fault-tolerant photonic computing systems.
文摘The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vision,Federated Learning(FL)has gained prominence as a distributed machine learning framework that allows multiple devices to collaboratively train models without sharing raw data,thereby preserving privacy and reducing the need for centralized storage.This capability is particularly attractive for vision-based applications,where image and video data are both sensitive and bandwidth-intensive.However,the integration of FL with 6G networks presents unique challenges,including communication bottlenecks,device heterogeneity,and trade-offs between model accuracy,latency,and energy consumption.In this paper,we developed a simulation-based framework to investigate the performance of FL in representative vision tasks under 6G-like environments.We formalize the system model,incorporating both the federated averaging(FedAvg)training process and a simplified communication costmodel that captures bandwidth constraints,packet loss,and variable latency across edge devices.Using standard image datasets(e.g.,MNIST,CIFAR-10)as benchmarks,we analyze how factors such as the number of participating clients,degree of data heterogeneity,and communication frequency influence convergence speed and model accuracy.Additionally,we evaluate the effectiveness of lightweight communication-efficient strategies,including local update tuning and gradient compression,in mitigating network overhead.The experimental results reveal several key insights:(i)communication limitations can significantly degrade FL convergence in vision tasks if not properly addressed;(ii)judicious tuning of local training epochs and client participation levels enables notable improvements in both efficiency and accuracy;and(iii)communication-efficient FL strategies provide a promising pathway to balance performance with the stringent latency and reliability requirements expected in 6G.These findings highlight the synergistic role of AI and nextgeneration networks in enabling privacy-preserving,real-time vision applications,and they provide concrete design guidelines for researchers and practitioners working at the intersection of FL and 6G.
基金funded by Youth Program of Shaanxi Provincial Department of Science and Technology(Grant No.2024JC-YBQN-0630)。
文摘Quantum key distribution(QKD)optical networks can provide more secure communications.However,with the increase of the QKD path requests and key updates,network blocking problems will become severe.The blocking problems in the network can become more severe because each fiber link has limited resources(such as wavelengths and time slots).In addition,QKD optical networks are also affected by external disturbances such as data interception and eavesdropping,resulting in inefficient network communication.In this paper,we exploit the idea of protection path to enhance the anti-interference ability of QKD optical network.By introducing the concept of security metric,we propose a routing wavelength and time slot allocation algorithm(RWTA)based on protection path,which can lessen the blocking problem of QKD optical network.According to simulation analysis,the security-metric-based RWTA algorithm(SM-RWTA)proposed in this paper can substantially improve the success rate of security key(SK)update and significantly reduce the blocking rate of the network.It can also improve the utilization rate of resources such as wavelengths and time slots.Compared with the non-security-metric-based RWTA algorithm(NSM-RWTA),our algorithm is robust and can enhance the anti-interference ability and security of QKD optical networks.
文摘Due to the increasing variety of information and services carried by optical networks, the survivability of network becomes an important problem in current research. The fault location of OTN is of great significance for studying the survivability of optical networks. Firstly, a three-channel network model is established and analyzing common alarm data, the fault monitoring points and common fault points are carried out. The artificial neural network is introduced into the fault location field of OTN and it is used to judge whether the possible fault point exists or not. But one of the obvious limitations of general neural networks is that they receive a fixedsize vector as input and produce a fixed-size vector as the output. Not only that, these models is even fixed for mapping operations (for example, the number of layers in the model). The difference between the recurrent neural network and general neural networks is that it can operate on the sequence. In spite of the fact that the gradient disappears and the gradient explodes still exist in the neural network, the method of gradient shearing or weight regularization is adopted to solve this problem, and choose the LSTM (long-short term memory networks) to locate the fault. The output uses the concept of membership degree of fuzzy theory to express the possible fault point with the probability from 0 to 1. Priority is given to the treatment of fault points with high probability. The concept of F-Measure is also introduced, and the positioning effect is measured by using location time, MSE and F-Measure. The experiment shows that both LSTM and BP neural network can locate the fault of optical transport network well, but the overall effect of LSTM is better. The localization time of LSTM is shorter than that of BP neural network, and the F1-score of LSTM can reach 0.961566888396156 after 45 iterations, which meets the accuracy and real-time requirements of fault location. Therefore, it has good application prospect and practical value to introduce neural network into the fault location field of optical transport network.
基金Supported by National Science Foundation of China(No.81800878)Interdisciplinary Program of Shanghai Jiao Tong University(No.YG2017QN24)+1 种基金Key Technological Research Projects of Songjiang District(No.18sjkjgg24)Bethune Langmu Ophthalmological Research Fund for Young and Middle-aged People(No.BJ-LM2018002J)
文摘AIM: To explore a segmentation algorithm based on deep learning to achieve accurate diagnosis and treatment of patients with retinal fluid.METHODS: A two-dimensional(2D) fully convolutional network for retinal segmentation was employed. In order to solve the category imbalance in retinal optical coherence tomography(OCT) images, the network parameters and loss function based on the 2D fully convolutional network were modified. For this network, the correlations of corresponding positions among adjacent images in space are ignored. Thus, we proposed a three-dimensional(3D) fully convolutional network for segmentation in the retinal OCT images.RESULTS: The algorithm was evaluated according to segmentation accuracy, Kappa coefficient, and F1 score. For the 3D fully convolutional network proposed in this paper, the overall segmentation accuracy rate is 99.56%, Kappa coefficient is 98.47%, and F1 score of retinal fluid is 95.50%. CONCLUSION: The OCT image segmentation algorithm based on deep learning is primarily founded on the 2D convolutional network. The 3D network architecture proposed in this paper reduces the influence of category imbalance, realizes end-to-end segmentation of volume images, and achieves optimal segmentation results. The segmentation maps are practically the same as the manual annotations of doctors, and can provide doctors with more accurate diagnostic data.
文摘An optical network is a type of data communication network built with optical fibre technology. It utilizes optical fibre cables as the primary communication medium for converting data and passing data as light pulses between sender and receiver nodes. The major issue in optical networking is disjoints that occur in the network. A polynomial time algorithm Wavelength Division Multiplexing-Passive Optical Networking (WDM-PON) computes disjoints of an optical network and reduces the count of disjoints that occur in the network by separating Optical Network Units (ONU) into several virtual point-to-point connections. The Arrayed Waveguide Grating (AWG) filter is included in WDM-PON to avoid the traffic in the network thereby increasing the bandwidth capacity. In case of a failure or disjoint Ant Colony Optimization (ACO) algorithm is used to find the optimized shortest path for re-routing. For enhanced security, modified Rivert Shamir Adleman (RSA) algorithm encrypts the message during communication between the nodes. The efficiency is found to be improved in terms of delay in packet delivery, longer optical reach, optimized shortest path, packet error rate.
基金extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through Project Number RI-44-0345.
文摘With the capacities of self-learning,acquainted capacities,high-speed looking for ideal arrangements,solid nonlin-ear fitting,and mapping self-assertively complex nonlinear relations,neural systems have made incredible advances and accomplished broad application over the final half-century.As one of the foremost conspicuous methods for fake insights,neural systems are growing toward high computational speed and moo control utilization.Due to the inborn impediments of electronic gadgets,it may be troublesome for electronic-implemented neural systems to make the strides these two exhibitions encourage.Optical neural systems can combine optoelectronic procedures and neural organization models to provide ways to break the bottleneck.This paper outlines optical neural networks of feedforward repetitive and spiking models to give a clearer picture of history,wildernesses,and future optical neural systems.The framework demonstrates neural systems in optic communication with the serial and parallel setup.The graphene-based laser structure for fiber optic communication is discussed.The comparison of different balance plans for photonic neural systems is made within the setting of hereditary calculation and molecule swarm optimization.In expansion,the execution comparison of routine photonic neural,time-domain with and without extending commotion is additionally expounded.The challenges and future patterns of optical neural systems on the growing scale and applications of in situ preparing nonlinear computing will hence be uncovered.
文摘An Extrinsic Fabry-Perot Interferometric (EFPI) fiber optical sensor system is an online testing system for the gas density. The system achieves the measurement of gas density information mainly by demodulating the cavity length of EF- PI fiber optical sensor. There are many ways to achieve the demodulation of the cavity length. For shortcomings of the big intensity demodulation error and complex structure of phase demodulation, this paper proposes that BP neural net-work is used to locate the special peak points in normalized interference spectrum and combining the advantages of the unimodal and bimodal measurement achieves the demodulation of the cavity length. Through online simulation and actual measurement, the results show that the peak positioning technology based on BP neural network can not only achieve high-precision demodulation of the cavity length, but also achieve an absolute measurement of cavity length in large dynamic range.
文摘One fiber radio scheme using shifted prime codes for interference elimination is proposed for optical code-division multiple-access (OCDMA) network. By taking advantage of the cyclic property of the shifted prime codes in the same code groups, the proposed compact decoder is low cost and suitable to be used in the task manager node in the applications of wireless sensor networks. The performance comparison for sev-eral OCDMA-based fiber radio networks is also given to clarify the advantage of the proposed one.
基金National Key R&D Program China under Grant 2018YFB1801701National Natural Science Foundation of China(NSFC)under Grant 61671313the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘Network virtualization is important for elastic optical networks(EONs)because of more flexible service provisioning.To ensure guaranteed quality of service(QoS)for each virtual elastic optical network(VEON),clients usually request network resources from a network operator based on their bandwidth requirements predicted from historical traffic demands.However,this may not be efficient as the actual traffic demands of users always fluctuate.To tackle this,we propose a new VEON service provisioning scheme,called SATP,which consists of three stages,i.e.,spectrum assignment(SA),spectrum trading(ST),and spectrum purchasing(SP).Unlike conventional once-for-all VEON service provisioning approaches,the SATP scheme first allocates spectrum resources to VEONs according to their predicted bandwidth requirements with a satisfaction ratio α(0<α≤1).Then,to minimize service degradation on VEONs which are short of assigned spectra for their peak traffic periods,the scheme allows VEONs to trade spectra with each other according to their actual bandwidth requirements.Finally,it allows VEON clients to purchase extra spectrum resources from a network operator if the spectrum resources are still insufficient.To optimize this entire process,we formulate the problem as a mixed integer linear programming(MILP)model and also develop efficient heuristic algorithms for each stage to handle large test scenarios.Simulations are conducted under different test conditions for both static and dynamic traffic demand scenarios.Results show that the proposed SATP scheme is efficient and can achieve significant performance improvement under both static and dynamic scenarios.
文摘A passive optical network （PON） scheme based on optical code division multiplexing （OCDM） for the downstream traffics is proposed and analyzed in detail. In the PON, the downstream traffics are broadcasted by OCDM technology to guarantee the security, while the upstream traffics pass through the same optical fiber by the common time division multiple access （TDMA） technology to decrease the cost. This schemes are denoted as OCDM/TDMA-PON, which can be applied to an optical access network （OAN） with full services on demand, such as Internet protocol, video on demand, tele-presence and high quality audio. The proposed OCDM/TDMA-PON scheme combines advantages of PON, TDMA, and OCDM technology. Simulation results indicate that the designed scheme improves the OAN performance, and enhances flexibility and scalability of the system.
基金Supported by the National Key Research and Development Program of China(No.2021YFB2401204)。
文摘As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model that makes full use of the gate recurrent unit(GRU)algorithm.Based on the fragmentation prediction model,one virtual optical network mapping scheme is presented for edge computing driven EON.With the minimum of fragmentation degree all over the whole EON,the virtual network mapping can be successively conducted.Test results show that the proposed approach can reduce blocking rate,and the supporting ability for virtual optical network services is greatly improved.
