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 off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to case...The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.展开更多
The network on chip（NoC）is used as a solution for the communication problems in a complex system on chip（SoC）design.To further enhance performances,the NoC architectures,a high level modeling and an evaluation met...The network on chip（NoC）is used as a solution for the communication problems in a complex system on chip（SoC）design.To further enhance performances,the NoC architectures,a high level modeling and an evaluation method based on OPNET are proposed to analyze their performances on different injection rates and traffic patterns.Simulation results for general NoC in terms of the average latency and the throughput are analyzed and used as a guideline to make appropriate choices for a given application.Finally,a MPEG4 decoder is mapped on different NoC architectures.Results prove the effectiveness of the evaluation method.展开更多
As the fifth-generation(5G)mobile communication network may not meet the requirements of emerging technologies and applications,including ubiquitous coverage,industrial internet of things(IIoT),ubiquitous artificial i...As the fifth-generation(5G)mobile communication network may not meet the requirements of emerging technologies and applications,including ubiquitous coverage,industrial internet of things(IIoT),ubiquitous artificial intelligence(AI),digital twins(DT),etc.,this paper aims to explore a novel space-air-ground integrated network(SAGIN)architecture to support these new requirements for the sixth-generation(6G)mobile communication network in a flexible,low-latency and efficient manner.Specifically,we first review the evolution of the mobile communication network,followed by the application and technology requirements of 6G.Then the current 5G non-terrestrial network(NTN)architecture in supporting the new requirements is deeply analyzed.After that,we proposes a new flexible,low-latency and flat SAGIN architecture,and presents corresponding use cases.Finally,the future research directions are discussed.展开更多
With the large-scale commercial launch of fifth generation(5G)mobile network,the development of new services and applications catering to the year 2030,along with the deep convergence of information,communication,and ...With the large-scale commercial launch of fifth generation(5G)mobile network,the development of new services and applications catering to the year 2030,along with the deep convergence of information,communication,and data technologies(ICDT),and the lessons and experiences from 5G practice will drive the evolution of the next generation of mobile networks.This article surveys the history and driving forces of the evolution of the mobile network architecture and proposes a logical function architecture for sixth generation(6G)mobile network.The proposed 6G network architecture is termed SOLIDS(related to the following basic features:soft,on-demand fulfillment,lite,native intelligence,digital twin,and native security),which can support self-generation,self-healing,self-evolution,and self-immunity without human involvement and address the primary issues in the legacy 5G network(e.g.,high cost,high power consumption,and highly complicated operation and maintenance),significantly well.展开更多
Along with the completion of the development of 4G technologies, the global mobile community starts the study of the next generation technologies, i.e. 5G technologies. This paper proposes a new flexible architecture ...Along with the completion of the development of 4G technologies, the global mobile community starts the study of the next generation technologies, i.e. 5G technologies. This paper proposes a new flexible architecture for 5G mobile networks based on Network Function Virtualization(NFV) and Software Defined Network(SDN) technologies, which is adaptable to use cases and scenarios. Then implementation reference architecture and some typical 5G network deployment cases are discussed. Besides, some key issues for further study are also indicated at the end.展开更多
Recently,due to the availability of big data and the rapid growth of computing power,artificial intelligence(AI)has regained tremendous attention and investment.Machine learning(ML)approaches have been successfully ap...Recently,due to the availability of big data and the rapid growth of computing power,artificial intelligence(AI)has regained tremendous attention and investment.Machine learning(ML)approaches have been successfully applied to solve many problems in academia and in industry.Although the explosion of big data applications is driving the development of ML,it also imposes severe challenges of data processing speed and scalability on conventional computer systems.Computing platforms that are dedicatedly designed for AI applications have been considered,ranging from a complement to von Neumann platforms to a“must-have”and stand-alone technical solution.These platforms,which belong to a larger category named“domain-specific computing,”focus on specific customization for AI.In this article,we focus on summarizing the recent advances in accelerator designs for deep neural networks(DNNs)-that is,DNN accelerators.We discuss various architectures that support DNN executions in terms of computing units,dataflow optimization,targeted network topologies,architectures on emerging technologies,and accelerators for emerging applications.We also provide our visions on the future trend of AI chip designs.展开更多
The space-air-ground integrated network(SAGIN) is regarded as the key approach to realize global coverage in future network and it reaches broad access for various services. Being the new paradigm of service, immersiv...The space-air-ground integrated network(SAGIN) is regarded as the key approach to realize global coverage in future network and it reaches broad access for various services. Being the new paradigm of service, immersive media(IM) has attracted users’ attention for its virtualization, but it poses challenges to network performance, e.g. bandwidth, rate, latency. However, the SAGIN has limitations in supporting IM services, such as 4 K/8 K video, virtual reality, and interactive games. In this paper, a novel service customized SAGIN architecture for IM applications(SAG-IM) is proposed, which achieves content interactive and real-time communication among terminal users. State-of-the-art research is investigated in detail to facilitate the combination of SAGIN and service customized technology, which provides endto-end differentiated services for users. Besides, the functional components of SAG-IM contain the infrastructure layer, perception layer, intelligence layer, and application layer, reaching the capabilities of intelligent management of the network. Moreover, to provide IM content with ultra-high-definition and high frame rate for the optimal user experience, the promising key technologies on intelligent routing and delivery are discussed. The performance evaluation shows the superiority of SAG-IM in supporting IM service.Finally, the prospects in practical application are high-lighted.展开更多
How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classif...How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.展开更多
The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate ev...The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate evaluation method does not make full use of the fuzzy information and uncertain information in the equipment system-of-systems(ESoS),and the Bayesian network is an effective tool to solve the uncertain information,a new ESoSA contribution rate evaluation method based on the fuzzy Bayesian network(FBN)is proposed.Firstly,based on the operation loop theory,an ESoSA is constructed considering three aspects:reconnaissance equipment,decision equipment,and strike equipment.Next,the fuzzy set theory is introduced to construct the FBN of ESoSA to deal with fuzzy information and uncertain information.Furthermore,the fuzzy importance index of the root node of the FBN is used to calculate the contribution rate of the ESoSA,and the ESoSA contribution rate evaluation model based on the root node fuzzy importance is established.Finally,the feasibility and rationality of this method are validated via an empirical case study of aviation ESoSA.Compared with traditional methods,the evaluation method based on FBN takes various failure states of equipment into consideration,is free of acquiring accurate probability of traditional equipment failure,and models the uncertainty of the relationship between equipment.The proposed method not only supplements and improves the ESoSA contribution rate assessment method,but also broadens the application scope of the Bayesian network.展开更多
1 Introduction The history of data centers can be traced back to the 1960s. Early data centers were deployed on main- frames that were time-shared by users via remote terminals. The boom in data centers came duringthe...1 Introduction The history of data centers can be traced back to the 1960s. Early data centers were deployed on main- frames that were time-shared by users via remote terminals. The boom in data centers came duringthe internet era. Many companies started building large inter- net-connected facililies,展开更多
Ethernet fundamental and its data transmission model are introduced in brief and end-to-end network latency was analyzed in this paper. On the premise of not considering transmission quality and transmission cost, lat...Ethernet fundamental and its data transmission model are introduced in brief and end-to-end network latency was analyzed in this paper. On the premise of not considering transmission quality and transmission cost, latency was the function of the rest of network resource parameter (NRP). The relation between the number of nodes and that of end-to-end links was presented. In ethernet architecture, the algorithm to determine the link with the smallest latency is a polynomial issue when the number of network nodes is limited, so it can be solved by way of polynomial equations. Latency measuring is the key issue to determine the link with the smallest network latency. 3-node brigade (regiment) level network centric warfare (NCW) demonstration platform was studied and the latency between the detectors and weapon control stations was taken as an example. The algorithm of end-to-end network latency and link information in NCW was presented. The algorithm program based on Server/Client architecture was developed. The data transmission optimal link is one whose end-to-end latency is the smallest. This paper solves the key issue to determine the link whose end-to-end latency is the smallest in ethernet architecture. The study can be widely applied to determine the optimal link which is in the complex network environment of multiple service provision points.展开更多
The prevalence of information appliances supporting DLNA (Digital Living Network Alliance) such as televisions, recorders, and mobile phones has made it possible to share digital contents (e.g. videos, music and pictu...The prevalence of information appliances supporting DLNA (Digital Living Network Alliance) such as televisions, recorders, and mobile phones has made it possible to share digital contents (e.g. videos, music and pictures) among appliances connected to a local network. However, DLNA does not let you share contents over different networks via the Internet. In this paper, we propose a network architecture where we adopt our SOAP method to mobile devices and use them as mobile gateways to consume digital contents from remote networks. We also confirm its practicality with a prototype.展开更多
Electromagnetic wave absorber is critical for reducing increasingly serious electromagnetic wave pollu-tion,however,the development of lightweight and broadband microwave absorbers remains a pressing challenge.We repo...Electromagnetic wave absorber is critical for reducing increasingly serious electromagnetic wave pollu-tion,however,the development of lightweight and broadband microwave absorbers remains a pressing challenge.We report here the rational design and synthesis of N-doped Ni@SiO_(2)/graphene composite con-structed from 3D interconnected porous graphene network and Ni@SiO_(2) core-shell architecture,which fulfills lightweight and broadband requirements while exhibiting highly efficient electromagnetic wave absorption.The porous graphene network,functioning both as lightweight support and dielectric medi-ator,was synthesized via NaCl template-assisted high-temperature calcination method.Upon uniformly attached with core-shell Ni@SiO_(2) on the surface,the resulting abundant heterogeneous interfaces con-structed by graphene-Ni and Ni-SiO_(2) strongly reinforce polarization loss.The presence of low dielectric SiO_(2) allows facile tuning of the complex permittivity of ternary composite by adjusting coating thick-ness to balance the attenuation ability and impedance matching.Moreover,further N-doping of graphene assists in the optimization of dielectric loss ability.Taking account of the advantages arising from the porous hierarchical architecture,multiple absorption centers and diverse interfaces,the lightweight com-posite exhibits an ultra-strong reflection loss(RL)value of-71.13 dB at 13.76 GHz with a thickness of 2.46 mm and broad effective absorption bandwidth of 7.04 GHz at a low filler content of 15 wt.%.More importantly,the effective absorption range covers 13.28 GHz(4.72-18 GHz)with the optimized thickness of 1.6-5 mm,representing 83%of the whole range of frequencies.Our results demonstrate that the novel 3D porous N-doped Ni@SiO_(2)/graphene network with hierarchical architecture is a promising candidate for high-performance electromagnetic wave absorption.展开更多
This paper presents an original probabilistic model of a hybrid underwater wireless sensor network(UWSN),which includes a network of stationary sensors placed on the seabed and a mobile gateway.The mobile gateway is a...This paper presents an original probabilistic model of a hybrid underwater wireless sensor network(UWSN),which includes a network of stationary sensors placed on the seabed and a mobile gateway.The mobile gateway is a wave glider that collects data from the underwater network segment and retransmits it to the processing center.The authors consider the joint problem of optimal localization of stationary network nodes and the corresponding model for bypassing reference nodes by a wave glider.The optimality of the network is evaluated according to the criteria of energy efficiency and reliability.The influence of various physical and technical parameters of the network on its energy efficiency and on the lifespan of sensor nodes is analyzed.The analysis is carried out for networks of various scales,depending on the localization of stationary nodes and the model of bypassing the network with a wave glider.As a model example,the simulation of the functional characteristics of the network for a given size of the water area is carried out.It is shown that in the case of a medium-sized water area,the model of“bypassing the perimeter”by a wave glider is practically feasible,energy efficient and reliable for hourly data measurements.In the case of a large water area,the cluster bypass model becomes more efficient.展开更多
5G is envisioned to guarantee high transmission rate,ultra-low latency,high reliability and massive connections.To satisfy the above requirements,the 5G architecture is designed with the properties of using service-ba...5G is envisioned to guarantee high transmission rate,ultra-low latency,high reliability and massive connections.To satisfy the above requirements,the 5G architecture is designed with the properties of using service-based architecture,cloud-native oriented,adopting IT-based API interfaces and introduction of the Network Repository Function.However,with the wide commercialization of 5G network and the exploration towards 6G,the 5G architecture exposes the disadvantages of high architecture complexity,difficult inter-interface communication,low cognitive capability,bad instantaneity,and deficient intelligence.To overcome these limitations,this paper investigates 6G network architecture,and proposes a cognitive intelligence based distributed 6G network architecture.This architecture consists of a physical network layer and an intelligent decision layer.The two layers coordinate through flexible service interfaces,supporting function decoupling and joint evolution of intelligence services and network services.With the above design,the proposed 6G architecture can be updated autonomously to deal with the future unpredicted complex services.展开更多
Operation architecture plays a more important role in Network Centric Warfare(NGAV),which involves dynamic operation networks with complex properties.Thus,it is essential to investigate the operation architecture unde...Operation architecture plays a more important role in Network Centric Warfare(NGAV),which involves dynamic operation networks with complex properties.Thus,it is essential to investigate the operation architecture under the informatization condition within NCAW and find a proper network construction method to efficiently coordinate various functional modules on a particular situation,i.e.,the aerial combat.A new method integrating the physical level and functional level of NCW is proposed to establish the operation architecture,where the concept of network operation constraints unit and net constructing mechanisms are employed to avoid conflicts among different platforms.Meanwhile,we conduct simulations to assess the effectiveness and feasibility of the constructed operation architecture and analyze the influence of the network parameters.展开更多
Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to ...Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to two issues:Both the hyperparameter and ar-chitecture should be optimised and the optimisation process is computationally expen-sive.To tackle these two issues,this paper focusses on solving the hyperparameter and architecture optimization problem for the NN and proposes a novel light‐weight scale‐adaptive fitness evaluation‐based particle swarm optimisation(SAFE‐PSO)approach.Firstly,the SAFE‐PSO algorithm considers the hyperparameters and architectures together in the optimisation problem and therefore can find their optimal combination for the globally best NN.Secondly,the computational cost can be reduced by using multi‐scale accuracy evaluation methods to evaluate candidates.Thirdly,a stagnation‐based switch strategy is proposed to adaptively switch different evaluation methods to better balance the search performance and computational cost.The SAFE‐PSO algorithm is tested on two widely used datasets:The 10‐category(i.e.,CIFAR10)and the 100−cate-gory(i.e.,CIFAR100).The experimental results show that SAFE‐PSO is very effective and efficient,which can not only find a promising NN automatically but also find a better NN than compared algorithms at the same computational cost.展开更多
In Internet of Things(IoT), the devices or terminals are connected with each other, which can be very diverse over the wireless networks. Unfortunately, the current devices are not designed to communicate with the col...In Internet of Things(IoT), the devices or terminals are connected with each other, which can be very diverse over the wireless networks. Unfortunately, the current devices are not designed to communicate with the collocated devices which employ different communication technologies. Consequently, the communication between these devices will be realized only by using the gateway nodes. This will cause the inefficient use of wireless resources. Therefore, in this paper, a smart service system(SSS) architecture is proposed, which consists of smart service terminal(SST), and smart service network(SSN), to realize the Io T in a general environment with diverse communication networks, devices, and services. The proposed architecture has the following advantages: i) the devices in this architecture cover multiple types of terminals and sensor-actuator devices; ii) the communications network therein is a converged network, and will coordinate multiple kinds of existing and emerging networks. This converged network offers ubiquitous access for various sensors and terminals; iii) the architecture has services and applications covering all smart service areas. It also provides theadaptability to new services and applications. A SSS architecture-based smart campus system was developed and deployed. Evaluation experiments of the proposed smart campus system demonstrate the SSS's advantages over the existing counterparts, and verify the effectiveness of the proposed architecture.展开更多
Plant disease classification based on digital pictures is challenging.Machine learning approaches and plant image categorization technologies such as deep learning have been utilized to recognize,identify,and diagnose...Plant disease classification based on digital pictures is challenging.Machine learning approaches and plant image categorization technologies such as deep learning have been utilized to recognize,identify,and diagnose plant diseases in the previous decade.Increasing the yield quantity and quality of rice forming is an important cause for the paddy production countries.However,some diseases that are blocking the improvement in paddy production are considered as an ominous threat.Convolution Neural Network(CNN)has shown a remarkable performance in solving the early detection of paddy leaf diseases based on its images in the fast-growing era of science and technology.Nevertheless,the significant CNN architectures construction is dependent on expertise in a neural network and domain knowledge.This approach is time-consuming,and high computational resources are mandatory.In this research,we propose a novel method based on Mutant Particle swarm optimization(MUT-PSO)Algorithms to search for an optimum CNN architecture for Paddy leaf disease classification.Experimentation results show that Mutant Particle swarm optimization Convolution Neural Network(MUTPSO-CNN)can find optimumCNNarchitecture that offers better performance than existing hand-crafted CNN architectures in terms of accuracy,precision/recall,and execution time.展开更多
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.
基金supported by the National Natural Science Foundation of China(No.12305344)the 2023 Anhui university research project of China(No.2023AH052179).
文摘The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.
基金Supported by the Natural Science Foundation of China(61076019)the China Postdoctoral Science Foundation(20100481134)+1 种基金the Natural Science Foundation of Jiangsu Province(BK2008387)the Graduate Student Innovation Foundation of Jiangsu Province(CX07B-105z)~~
文摘The network on chip（NoC）is used as a solution for the communication problems in a complex system on chip（SoC）design.To further enhance performances,the NoC architectures,a high level modeling and an evaluation method based on OPNET are proposed to analyze their performances on different injection rates and traffic patterns.Simulation results for general NoC in terms of the average latency and the throughput are analyzed and used as a guideline to make appropriate choices for a given application.Finally,a MPEG4 decoder is mapped on different NoC architectures.Results prove the effectiveness of the evaluation method.
基金supported in part by the National Key Research and Development Program under grant number 2020YFB1806800the Beijing Natural Science Foundation under grant number L212003the National Natural Science Foundation of China(NSFC)under grant numbers 62171010 and 61827901.
文摘As the fifth-generation(5G)mobile communication network may not meet the requirements of emerging technologies and applications,including ubiquitous coverage,industrial internet of things(IIoT),ubiquitous artificial intelligence(AI),digital twins(DT),etc.,this paper aims to explore a novel space-air-ground integrated network(SAGIN)architecture to support these new requirements for the sixth-generation(6G)mobile communication network in a flexible,low-latency and efficient manner.Specifically,we first review the evolution of the mobile communication network,followed by the application and technology requirements of 6G.Then the current 5G non-terrestrial network(NTN)architecture in supporting the new requirements is deeply analyzed.After that,we proposes a new flexible,low-latency and flat SAGIN architecture,and presents corresponding use cases.Finally,the future research directions are discussed.
基金the National Key Research and Development Program of China(2020YFB1806800).
文摘With the large-scale commercial launch of fifth generation(5G)mobile network,the development of new services and applications catering to the year 2030,along with the deep convergence of information,communication,and data technologies(ICDT),and the lessons and experiences from 5G practice will drive the evolution of the next generation of mobile networks.This article surveys the history and driving forces of the evolution of the mobile network architecture and proposes a logical function architecture for sixth generation(6G)mobile network.The proposed 6G network architecture is termed SOLIDS(related to the following basic features:soft,on-demand fulfillment,lite,native intelligence,digital twin,and native security),which can support self-generation,self-healing,self-evolution,and self-immunity without human involvement and address the primary issues in the legacy 5G network(e.g.,high cost,high power consumption,and highly complicated operation and maintenance),significantly well.
基金supported by the National Science and Technology Major Project No.2015ZX03002004
文摘Along with the completion of the development of 4G technologies, the global mobile community starts the study of the next generation technologies, i.e. 5G technologies. This paper proposes a new flexible architecture for 5G mobile networks based on Network Function Virtualization(NFV) and Software Defined Network(SDN) technologies, which is adaptable to use cases and scenarios. Then implementation reference architecture and some typical 5G network deployment cases are discussed. Besides, some key issues for further study are also indicated at the end.
基金the National Science Foundations(NSFs)(1822085,1725456,1816833,1500848,1719160,and 1725447)the NSF Computing and Communication Foundations(1740352)+1 种基金the Nanoelectronics COmputing REsearch Program in the Semiconductor Research Corporation(NC-2766-A)the Center for Research in Intelligent Storage and Processing-in-Memory,one of six centers in the Joint University Microelectronics Program,a SRC program sponsored by Defense Advanced Research Projects Agency.
文摘Recently,due to the availability of big data and the rapid growth of computing power,artificial intelligence(AI)has regained tremendous attention and investment.Machine learning(ML)approaches have been successfully applied to solve many problems in academia and in industry.Although the explosion of big data applications is driving the development of ML,it also imposes severe challenges of data processing speed and scalability on conventional computer systems.Computing platforms that are dedicatedly designed for AI applications have been considered,ranging from a complement to von Neumann platforms to a“must-have”and stand-alone technical solution.These platforms,which belong to a larger category named“domain-specific computing,”focus on specific customization for AI.In this article,we focus on summarizing the recent advances in accelerator designs for deep neural networks(DNNs)-that is,DNN accelerators.We discuss various architectures that support DNN executions in terms of computing units,dataflow optimization,targeted network topologies,architectures on emerging technologies,and accelerators for emerging applications.We also provide our visions on the future trend of AI chip designs.
基金supported by the National Key Research and Development Program of China (No.2019YFB1803103)in part by the BUPT Excellent Ph.D. Students Foundation (No.CX2021113)。
文摘The space-air-ground integrated network(SAGIN) is regarded as the key approach to realize global coverage in future network and it reaches broad access for various services. Being the new paradigm of service, immersive media(IM) has attracted users’ attention for its virtualization, but it poses challenges to network performance, e.g. bandwidth, rate, latency. However, the SAGIN has limitations in supporting IM services, such as 4 K/8 K video, virtual reality, and interactive games. In this paper, a novel service customized SAGIN architecture for IM applications(SAG-IM) is proposed, which achieves content interactive and real-time communication among terminal users. State-of-the-art research is investigated in detail to facilitate the combination of SAGIN and service customized technology, which provides endto-end differentiated services for users. Besides, the functional components of SAG-IM contain the infrastructure layer, perception layer, intelligence layer, and application layer, reaching the capabilities of intelligent management of the network. Moreover, to provide IM content with ultra-high-definition and high frame rate for the optimal user experience, the promising key technologies on intelligent routing and delivery are discussed. The performance evaluation shows the superiority of SAG-IM in supporting IM service.Finally, the prospects in practical application are high-lighted.
基金supported by the National Natural Science Foundation of China(U1435220)
文摘How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.
基金supported by the National Key Research and Development Project(2018YFB1700802)the National Natural Science Foundation of China(72071206)the Science and Technology Innovation Plan of Hunan Province(2020RC4046).
文摘The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate evaluation method does not make full use of the fuzzy information and uncertain information in the equipment system-of-systems(ESoS),and the Bayesian network is an effective tool to solve the uncertain information,a new ESoSA contribution rate evaluation method based on the fuzzy Bayesian network(FBN)is proposed.Firstly,based on the operation loop theory,an ESoSA is constructed considering three aspects:reconnaissance equipment,decision equipment,and strike equipment.Next,the fuzzy set theory is introduced to construct the FBN of ESoSA to deal with fuzzy information and uncertain information.Furthermore,the fuzzy importance index of the root node of the FBN is used to calculate the contribution rate of the ESoSA,and the ESoSA contribution rate evaluation model based on the root node fuzzy importance is established.Finally,the feasibility and rationality of this method are validated via an empirical case study of aviation ESoSA.Compared with traditional methods,the evaluation method based on FBN takes various failure states of equipment into consideration,is free of acquiring accurate probability of traditional equipment failure,and models the uncertainty of the relationship between equipment.The proposed method not only supplements and improves the ESoSA contribution rate assessment method,but also broadens the application scope of the Bayesian network.
基金supported by the ZTE-BJTU Collaborative Research Program under Grant No. K11L00190the Fundamental Research Funds for the Central Universities under Grant No. K12JB00060
文摘1 Introduction The history of data centers can be traced back to the 1960s. Early data centers were deployed on main- frames that were time-shared by users via remote terminals. The boom in data centers came duringthe internet era. Many companies started building large inter- net-connected facililies,
基金Sponsored by Grand Preresearch Project Foundation of General Armament Department of the CPLAin the Tenth Five-year Plan (Grant No41306020202)the National Natural Science Foundation of China(Grant No60672150)
文摘Ethernet fundamental and its data transmission model are introduced in brief and end-to-end network latency was analyzed in this paper. On the premise of not considering transmission quality and transmission cost, latency was the function of the rest of network resource parameter (NRP). The relation between the number of nodes and that of end-to-end links was presented. In ethernet architecture, the algorithm to determine the link with the smallest latency is a polynomial issue when the number of network nodes is limited, so it can be solved by way of polynomial equations. Latency measuring is the key issue to determine the link with the smallest network latency. 3-node brigade (regiment) level network centric warfare (NCW) demonstration platform was studied and the latency between the detectors and weapon control stations was taken as an example. The algorithm of end-to-end network latency and link information in NCW was presented. The algorithm program based on Server/Client architecture was developed. The data transmission optimal link is one whose end-to-end latency is the smallest. This paper solves the key issue to determine the link whose end-to-end latency is the smallest in ethernet architecture. The study can be widely applied to determine the optimal link which is in the complex network environment of multiple service provision points.
文摘The prevalence of information appliances supporting DLNA (Digital Living Network Alliance) such as televisions, recorders, and mobile phones has made it possible to share digital contents (e.g. videos, music and pictures) among appliances connected to a local network. However, DLNA does not let you share contents over different networks via the Internet. In this paper, we propose a network architecture where we adopt our SOAP method to mobile devices and use them as mobile gateways to consume digital contents from remote networks. We also confirm its practicality with a prototype.
基金supported by the National Natural Science Foundation of China (Nos.91963204 and 51871053)Shanghai Pujiang Program (No.19PJ1400200)the Fundamental Research Funds for the Central Universities (Nos.2232019G-07 and 2232020A-02)。
文摘Electromagnetic wave absorber is critical for reducing increasingly serious electromagnetic wave pollu-tion,however,the development of lightweight and broadband microwave absorbers remains a pressing challenge.We report here the rational design and synthesis of N-doped Ni@SiO_(2)/graphene composite con-structed from 3D interconnected porous graphene network and Ni@SiO_(2) core-shell architecture,which fulfills lightweight and broadband requirements while exhibiting highly efficient electromagnetic wave absorption.The porous graphene network,functioning both as lightweight support and dielectric medi-ator,was synthesized via NaCl template-assisted high-temperature calcination method.Upon uniformly attached with core-shell Ni@SiO_(2) on the surface,the resulting abundant heterogeneous interfaces con-structed by graphene-Ni and Ni-SiO_(2) strongly reinforce polarization loss.The presence of low dielectric SiO_(2) allows facile tuning of the complex permittivity of ternary composite by adjusting coating thick-ness to balance the attenuation ability and impedance matching.Moreover,further N-doping of graphene assists in the optimization of dielectric loss ability.Taking account of the advantages arising from the porous hierarchical architecture,multiple absorption centers and diverse interfaces,the lightweight com-posite exhibits an ultra-strong reflection loss(RL)value of-71.13 dB at 13.76 GHz with a thickness of 2.46 mm and broad effective absorption bandwidth of 7.04 GHz at a low filler content of 15 wt.%.More importantly,the effective absorption range covers 13.28 GHz(4.72-18 GHz)with the optimized thickness of 1.6-5 mm,representing 83%of the whole range of frequencies.Our results demonstrate that the novel 3D porous N-doped Ni@SiO_(2)/graphene network with hierarchical architecture is a promising candidate for high-performance electromagnetic wave absorption.
基金The research was partially funded by the Ministry of Science and Higher Education of the Russian Federation as part of World-class Research Center program:Advanced Digital Technologies(Contract No.075-15-2020-903 dated 16.11.2020).
文摘This paper presents an original probabilistic model of a hybrid underwater wireless sensor network(UWSN),which includes a network of stationary sensors placed on the seabed and a mobile gateway.The mobile gateway is a wave glider that collects data from the underwater network segment and retransmits it to the processing center.The authors consider the joint problem of optimal localization of stationary network nodes and the corresponding model for bypassing reference nodes by a wave glider.The optimality of the network is evaluated according to the criteria of energy efficiency and reliability.The influence of various physical and technical parameters of the network on its energy efficiency and on the lifespan of sensor nodes is analyzed.The analysis is carried out for networks of various scales,depending on the localization of stationary nodes and the model of bypassing the network with a wave glider.As a model example,the simulation of the functional characteristics of the network for a given size of the water area is carried out.It is shown that in the case of a medium-sized water area,the model of“bypassing the perimeter”by a wave glider is practically feasible,energy efficient and reliable for hourly data measurements.In the case of a large water area,the cluster bypass model becomes more efficient.
基金funded by Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center,the National Key R&D Program of China(2018YFE0205503)the National Natural Science Foundation of China(61902036,62032003,61922017)Fundamental Research Funds for the Central Universities。
文摘5G is envisioned to guarantee high transmission rate,ultra-low latency,high reliability and massive connections.To satisfy the above requirements,the 5G architecture is designed with the properties of using service-based architecture,cloud-native oriented,adopting IT-based API interfaces and introduction of the Network Repository Function.However,with the wide commercialization of 5G network and the exploration towards 6G,the 5G architecture exposes the disadvantages of high architecture complexity,difficult inter-interface communication,low cognitive capability,bad instantaneity,and deficient intelligence.To overcome these limitations,this paper investigates 6G network architecture,and proposes a cognitive intelligence based distributed 6G network architecture.This architecture consists of a physical network layer and an intelligent decision layer.The two layers coordinate through flexible service interfaces,supporting function decoupling and joint evolution of intelligence services and network services.With the above design,the proposed 6G architecture can be updated autonomously to deal with the future unpredicted complex services.
基金fully supported by a grant from the National Natural Science Foundation of China(No.61472443)。
文摘Operation architecture plays a more important role in Network Centric Warfare(NGAV),which involves dynamic operation networks with complex properties.Thus,it is essential to investigate the operation architecture under the informatization condition within NCAW and find a proper network construction method to efficiently coordinate various functional modules on a particular situation,i.e.,the aerial combat.A new method integrating the physical level and functional level of NCW is proposed to establish the operation architecture,where the concept of network operation constraints unit and net constructing mechanisms are employed to avoid conflicts among different platforms.Meanwhile,we conduct simulations to assess the effectiveness and feasibility of the constructed operation architecture and analyze the influence of the network parameters.
基金supported in part by the National Key Research and Development Program of China under Grant 2019YFB2102102in part by the National Natural Science Foundations of China under Grant 62176094 and Grant 61873097+2 种基金in part by the Key‐Area Research and Development of Guangdong Province under Grant 2020B010166002in part by the Guangdong Natural Science Foundation Research Team under Grant 2018B030312003in part by the Guangdong‐Hong Kong Joint Innovation Platform under Grant 2018B050502006.
文摘Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to two issues:Both the hyperparameter and ar-chitecture should be optimised and the optimisation process is computationally expen-sive.To tackle these two issues,this paper focusses on solving the hyperparameter and architecture optimization problem for the NN and proposes a novel light‐weight scale‐adaptive fitness evaluation‐based particle swarm optimisation(SAFE‐PSO)approach.Firstly,the SAFE‐PSO algorithm considers the hyperparameters and architectures together in the optimisation problem and therefore can find their optimal combination for the globally best NN.Secondly,the computational cost can be reduced by using multi‐scale accuracy evaluation methods to evaluate candidates.Thirdly,a stagnation‐based switch strategy is proposed to adaptively switch different evaluation methods to better balance the search performance and computational cost.The SAFE‐PSO algorithm is tested on two widely used datasets:The 10‐category(i.e.,CIFAR10)and the 100−cate-gory(i.e.,CIFAR100).The experimental results show that SAFE‐PSO is very effective and efficient,which can not only find a promising NN automatically but also find a better NN than compared algorithms at the same computational cost.
基金supported by the national 973 project of China under Grants 2013CB329104the Natural Science Foundation of China under Grants 61372124, 61427801+1 种基金the Natural Science Foundation of the Jiangsu Higher Education Institutions (Grant No.13KJB520029)the Jiangsu Province colleges and universities graduate students scientific research and innovation program CXZZ13_0477,NUPTSF(Grant No.NY214033)
文摘In Internet of Things(IoT), the devices or terminals are connected with each other, which can be very diverse over the wireless networks. Unfortunately, the current devices are not designed to communicate with the collocated devices which employ different communication technologies. Consequently, the communication between these devices will be realized only by using the gateway nodes. This will cause the inefficient use of wireless resources. Therefore, in this paper, a smart service system(SSS) architecture is proposed, which consists of smart service terminal(SST), and smart service network(SSN), to realize the Io T in a general environment with diverse communication networks, devices, and services. The proposed architecture has the following advantages: i) the devices in this architecture cover multiple types of terminals and sensor-actuator devices; ii) the communications network therein is a converged network, and will coordinate multiple kinds of existing and emerging networks. This converged network offers ubiquitous access for various sensors and terminals; iii) the architecture has services and applications covering all smart service areas. It also provides theadaptability to new services and applications. A SSS architecture-based smart campus system was developed and deployed. Evaluation experiments of the proposed smart campus system demonstrate the SSS's advantages over the existing counterparts, and verify the effectiveness of the proposed architecture.
基金The authors received funding source for this research activity under Multi-Disciplinary Research(MDR)Grant Vot H483 from Research Management Centre(RMC)office,Universiti Tun Hussein Onn Malaysia(UTHM).
文摘Plant disease classification based on digital pictures is challenging.Machine learning approaches and plant image categorization technologies such as deep learning have been utilized to recognize,identify,and diagnose plant diseases in the previous decade.Increasing the yield quantity and quality of rice forming is an important cause for the paddy production countries.However,some diseases that are blocking the improvement in paddy production are considered as an ominous threat.Convolution Neural Network(CNN)has shown a remarkable performance in solving the early detection of paddy leaf diseases based on its images in the fast-growing era of science and technology.Nevertheless,the significant CNN architectures construction is dependent on expertise in a neural network and domain knowledge.This approach is time-consuming,and high computational resources are mandatory.In this research,we propose a novel method based on Mutant Particle swarm optimization(MUT-PSO)Algorithms to search for an optimum CNN architecture for Paddy leaf disease classification.Experimentation results show that Mutant Particle swarm optimization Convolution Neural Network(MUTPSO-CNN)can find optimumCNNarchitecture that offers better performance than existing hand-crafted CNN architectures in terms of accuracy,precision/recall,and execution time.
