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Container cluster placement in edge computing based on reinforcement learning incorporating graph convolutional networks scheme 认领 引用 被引量：1
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作者 Zhuo Chen Bowen Zhu Chuan Zhou 《Digital Communications and Networks》 SCIE EI CSCD 2025年第1期60-70,共11页
Container-based virtualization technology has been more widely used in edge computing environments recently due to its advantages of lighter resource occupation, faster startup capability, and better resource utilizat... Container-based virtualization technology has been more widely used in edge computing environments recently due to its advantages of lighter resource occupation, faster startup capability, and better resource utilization efficiency. To meet the diverse needs of tasks, it usually needs to instantiate multiple network functions in the form of containers interconnect various generated containers to build a Container Cluster(CC). Then CCs will be deployed on edge service nodes with relatively limited resources. However, the increasingly complex and timevarying nature of tasks brings great challenges to optimal placement of CC. This paper regards the charges for various resources occupied by providing services as revenue, the service efficiency and energy consumption as cost, thus formulates a Mixed Integer Programming(MIP) model to describe the optimal placement of CC on edge service nodes. Furthermore, an Actor-Critic based Deep Reinforcement Learning(DRL) incorporating Graph Convolutional Networks(GCN) framework named as RL-GCN is proposed to solve the optimization problem. The framework obtains an optimal placement strategy through self-learning according to the requirements and objectives of the placement of CC. Particularly, through the introduction of GCN, the features of the association relationship between multiple containers in CCs can be effectively extracted to improve the quality of placement.The experiment results show that under different scales of service nodes and task requests, the proposed method can obtain the improved system performance in terms of placement error ratio, time efficiency of solution output and cumulative system revenue compared with other representative baseline methods. 展开更多
关键词 Edge computing Network virtualization Container cluster Deep reinforcement learning Graph convolutional network
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Virtualization Technology in Cloud Computing Based Radio Access Networks:A Primer 认领 引用 被引量：2
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作者 ZHANG Xian PENG Mugen 《ZTE Communications》 2017年第4期47-66,共20页
Since virtualization technology enables the abstraction and sharing of resources in a flexible management way, the overall expenses of network deployment can be significantly reduced. Therefore, the technology has bee... Since virtualization technology enables the abstraction and sharing of resources in a flexible management way, the overall expenses of network deployment can be significantly reduced. Therefore, the technology has been widely applied in the core network. With the tremendous growth in mobile traffic and services, it is natural to extend virtualization technology to the cloud computing based radio access networks(CCRANs) for achieving high spectral efficiency with low cost.In this paper, the virtualization technologies in CC-RANs are surveyed, including the system architecture, key enabling techniques, challenges, and open issues. The enabling key technologies for virtualization in CC-RANs mainly including virtual resource allocation, radio access network(RAN) slicing, mobility management, and social-awareness have been comprehensively surveyed to satisfy the isolation, customization and high-efficiency utilization of radio resources. The challenges and open issues mainly focus on virtualization levels for CC-RANs, signaling design for CC-RAN virtualization, performance analysis for CC-RAN virtualization, and network security for virtualized CC-RANs. 展开更多
关键词 network virtualization CC-RAN RAN slicing fog computing
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Edge computing oriented virtual optical network mapping scheme based on fragmentation prediction 认领 引用
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作者 何烁 BAI Huifeng +1 位作者 HUO Chao ZHANG Ganghong 《High Technology Letters》 EI CAS 2024年第2期158-163,共6页
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
关键词 elastic optical networks virtual optical network fragmentation self-awareness edge computing
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A Review in the Core Technologies of 5G: Device-to-Device Communication, Multi-Access Edge Computing and Network Function Virtualization 认领 引用 被引量：3
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作者 Ruixuan Tu Ruxun Xiang +1 位作者 Yang Xu Yihan Mei 《International Journal of Communications, Network and System Sciences》 2019年第9期125-150,共26页
5G is a new generation of mobile networking that aims to achieve unparalleled speed and performance. To accomplish this, three technologies, Device-to-Device communication (D2D), multi-access edge computing (MEC) and ... 5G is a new generation of mobile networking that aims to achieve unparalleled speed and performance. To accomplish this, three technologies, Device-to-Device communication (D2D), multi-access edge computing (MEC) and network function virtualization (NFV) with ClickOS, have been a significant part of 5G, and this paper mainly discusses them. D2D enables direct communication between devices without the relay of base station. In 5G, a two-tier cellular network composed of traditional cellular network system and D2D is an efficient method for realizing high-speed communication. MEC unloads work from end devices and clouds platforms to widespread nodes, and connects the nodes together with outside devices and third-party providers, in order to diminish the overloading effect on any device caused by enormous applications and improve users’ quality of experience (QoE). There is also a NFV method in order to fulfill the 5G requirements. In this part, an optimized virtual machine for middle-boxes named ClickOS is introduced, and it is evaluated in several aspects. Some middle boxes are being implemented in the ClickOS and proved to have outstanding performances. 展开更多
关键词 5th Generation Network Virtualization Device-To-Device communication Base Station Direct Communication Interference Multi-Access Edge Computing Mobile Edge Computing
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Heuristic Scheduling Algorithms for Allocation of Virtualized Network and Computing Resources 认领 引用
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作者 Yichao Yang Yanbo Zhou +1 位作者 Zhili Sun Haitham Cruickshank 《Journal of Software Engineering and Applications》 2013年第1期1-13,共13页
Cloud computing technology facilitates computing-intensive applications by providing virtualized resources which can be dynamically provisioned. However, user’s requests are varied according to different applications... Cloud computing technology facilitates computing-intensive applications by providing virtualized resources which can be dynamically provisioned. However, user’s requests are varied according to different applications’ computation ability needs. These applications can be presented as meta-job of user’s demand. The total processing time of these jobs may need data transmission time over the Internet as well as the completed time of jobs to execute on the virtual machine must be taken into account. In this paper, we presented V-heuristics scheduling algorithm for allocation of virtualized network and computing resources under user’s constraint which applied into a service-oriented resource broker for jobs scheduling. This scheduling algorithm takes into account both data transmission time and computation time that related to virtualized network and virtual machine. The simulation results are compared with three different types of heuristic algorithms under conventional network or virtual network conditions such as MCT, Min-Min and Max-Min. e evaluate these algorithms within a simulated cloud environment via an abilenenetwork topology which is real physical core network topology. These experimental results show that V-heuristic scheduling algorithm achieved significant performance gain for a variety of applications in terms of load balance, Makespan, average resource utilization and total processing time. 展开更多
关键词 Cloud Computing Meta-Job Scheduling Heuristic Algorithm Load Balance Network Virtualization
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Effective Edge-Cloud Interplay for NFV-Based Optical Metro-Access Networks Supporting IoT Services 认领 引用 被引量：2
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作者 Jin Feiming Zhang Yukun +2 位作者 Li Hanxue Amr Tolba Zhang Tiantian 《China Communications》 SCIE EI CSCD 2025年第4期117-128,共12页
In optical metro-access networks,Access Points(APs)and Data Centers(DCs)are located on the fiber ring.In the cloud-centric solution,a large number of Internet of Things(IoT)data pose an enormous burden on DCs,so the V... In optical metro-access networks,Access Points(APs)and Data Centers(DCs)are located on the fiber ring.In the cloud-centric solution,a large number of Internet of Things(IoT)data pose an enormous burden on DCs,so the Virtual Machines(VMs)cannot be successfully launched due to the server overload.In addition,transferring the data from the AP to the remote DC may cause an undesirable delivery delay.For this end,we propose a promising solution considering the interplay between the cloud DC and edge APs.More specifically,bringing the partial capability of computing in APs close to things can reduce the pressure of DCs while guaranteeing the expected Quality of Service(QoS).In this work,when the cloud DC resource becomes limited,especially for delay sensitive but not computing-dependent IoT applications,we degrade their VMs and migrate them to edge APs instead of the remote DC.To avoid excessive VM degradation and computing offloading,we derive appropriate VM degradation coefficients based on classic microeconomic theory.Simulation results demonstrate that our algorithms improve the service providers'utility with the ratio from 34%to 89%over traditional cloud-centric solutions. 展开更多
关键词 computing offloading edge-cloud interplay network function virtualization optical metroaccess network service degradability
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A New Reliable System For Managing Virtual Cloud Network 认领 引用
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作者 Samah Alshathri Fatma M.Talaat Aida A.Nasr 《Computers, Materials & Continua》 SCIE EI 2022年第12期5863-5885,共23页
Virtual cloud network(VCN)usage is popular today among large and small organizations due to its safety and money-saving.Moreover,it makes all resources in the company work as one unit.VCN also facilitates sharing of f... Virtual cloud network(VCN)usage is popular today among large and small organizations due to its safety and money-saving.Moreover,it makes all resources in the company work as one unit.VCN also facilitates sharing of files and applications without effort.However,cloud providers face many issues in managing the VCN on cloud computing including these issues:Power consumption,network failures,and data availability.These issues often occur due to overloaded and unbalanced load tasks.In this paper,we propose a new automatic system to manage VCN for executing the workflow.The new system calledMulti-User Hybrid Scheduling(MUSH)can solve running issues and save power during workflow execution.It consists of three phases:Initialization,virtual machine allocation,and task scheduling algorithms.The MUSH system focuses on the execution of the workflow with deadline constraints.Moreover,it considers the utilization of virtual machines.The new system can save makespan and increase the throughput of the execution operation. 展开更多
关键词 Virtual network scheduling reliability VM allocation cloud computing
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Energy Efficient and Resource Allocation in Cloud Computing Using QT-DNN and Binary Bird Swarm Optimization 认领 引用
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作者 Puneet Sharma Dhirendra Prasad Yadav +2 位作者 Bhisham Sharma Surbhi B.Khan Ahlam Almusharraf 《Computers, Materials & Continua》 SCIE EI 2025年第10期2179-2193,共15页
The swift expansion of cloud computing has heightened the demand for energy-efficient and high-performance resource allocation solutions across extensive systems.This research presents an innovative hybrid framework t... The swift expansion of cloud computing has heightened the demand for energy-efficient and high-performance resource allocation solutions across extensive systems.This research presents an innovative hybrid framework that combines a Quantum Tensor-based Deep Neural Network(QT-DNN)with Binary Bird Swarm Optimization(BBSO)to enhance resource allocation while preserving Quality of Service(QoS).In contrast to conventional approaches,the QT-DNN accurately predicts task-resource mappings using tensor-based task representation,significantly minimizing computing overhead.The BBSO allocates resources dynamically,optimizing energy efficiency and task distribution.Experimental results from extensive simulations indicate the efficacy of the suggested strategy;the proposed approach demonstrates the highest level of accuracy,reaching 98.1%.This surpasses the GA-SVM model,which achieves an accuracy of 96.3%,and the ART model,which achieves an accuracy of 95.4%.The proposed method performs better in terms of response time with 1.598 as compared to existing methods Energy-Focused Dynamic Task Scheduling(EFDTS)and Federated Energy-efficient Scheduler for Task Allocation in Large-scale environments(FESTAL)with 2.31 and 2.04,moreover,the proposed method performs better in terms of makespan with 12 as compared to Round Robin(RR)and Recurrent Attention-based Summarization Algorithm(RASA)with 20 and 14.The hybrid method establishes a new standard for sustainable and efficient administration of cloud computing resources by explicitly addressing scalability and real-time performance. 展开更多
关键词 Cloud computing quality of service virtual machine allocation deep neural network
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轻量级虚拟化技术安全研究综述 认领 引用
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作者 孔同 王利明 +1 位作者 徐震 马多贺 《信息安全学报》 CSCD 2026年第2期273-288,共16页
随着以容器技术为代表的轻量级虚拟化技术飞速发展,其在云计算领域中的地位也越来越重要。轻量级虚拟化技术不为虚拟实例创建单独的操作系统,而是使用各种内核机制来进行实现CPU、内存、网络和文件系统的隔离,可以更高效、灵活地实现硬... 随着以容器技术为代表的轻量级虚拟化技术飞速发展,其在云计算领域中的地位也越来越重要。轻量级虚拟化技术不为虚拟实例创建单独的操作系统,而是使用各种内核机制来进行实现CPU、内存、网络和文件系统的隔离,可以更高效、灵活地实现硬件基础设施资源的充分利用、合理分配和有效调度,为云计算带来了云原生等新的技术架构和运维模式。同时由于同一宿主机上的轻量化虚拟实例间共享操作系统内核、缺乏针对镜像库的有效检测手段等,轻量级虚拟化技术相较于传统虚拟机技术安全隔离手段较弱且引入了新的安全风险,为云计算技术带来了新的安全挑战,引起学术界和工业界的广泛关注,但其安全性缺少系统性的研究。为体系化了解轻量级虚拟化技术的安全研究进展和现状,本文对轻量级虚拟化技术的安全问题以及解决方案进行了深入研究分析。首先对轻量级虚拟化技术的架构特点和应用场景进行了概述,按照分层模型对轻量级虚拟实例层、宿主机层及硬件层等对象面临的攻击威胁进行了分类综述,并概述了镜像库及其他配套系统存在的安全脆弱性。然后,根据安全解决方案所属的系统层次对已有的安全防御方法和机制进行了深入介绍,并对其防御原理、可应对的网络攻击类型、实现方案及优缺点进行了详细分析和总结。最后,展望了轻量级虚拟化技术安全未来的发展趋势和后续的研究方向,认为强化虚拟隔离、保障镜像安全检测、统一安全评估技术标准是提高轻量级虚拟化技术安全性的有效方法。 展开更多
关键词 云计算 轻量级虚拟化 容器技术 网络安全
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SICN:天基智能云网体系架构设想 认领 引用
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作者 虞志刚 李朕 +3 位作者 章扬 龚恺 李果 朱雪田 《天地一体化信息网络》 2026年第2期11-21,共11页
随着太空探索与利用的智能化进程不断加速,以星链、逐日者等为代表的项目已开始布局天基数据中心建设。在此背景下,如何将通信、导航、遥感、计算、存储等多维资源深度融合,构建统一、高效的天基信息基础设施,已成为国内外工业界和学术... 随着太空探索与利用的智能化进程不断加速,以星链、逐日者等为代表的项目已开始布局天基数据中心建设。在此背景下,如何将通信、导航、遥感、计算、存储等多维资源深度融合,构建统一、高效的天基信息基础设施,已成为国内外工业界和学术界共同关注的关键课题。以天基云计算与虚拟化技术为基础,面向未来天基信息系统的实际需求,提出一种具备弹性可扩展、资源共享、信息融合与服务敏捷等特征的“天基智能云网”体系架构,并针对动态组网、星地协同、高可靠计算等挑战,系统剖析了相应的关键使能技术,以期为我国构建自主可控的空间信息基础设施提供重要支撑。 展开更多
关键词 天基计算 云计算 云网融合 虚拟化
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“四新”背景下计算机网络实验教学体系的构建与实践研究 认领 引用
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作者 韦忠亮 葛斌 蒋社想 《淮阴工学院学报》 CAS 2026年第2期97-104,共8页
“四新”教育理念深化实施与新工科建设工程推进的背景下,作为计算机科学与技术专业的核心课程实验,计算机网络实验面临教学内容相对滞后、实验平台单一、课程评价体系不完善等问题。以安徽理工大学计算机科学与工程学院开设的计算机网... “四新”教育理念深化实施与新工科建设工程推进的背景下,作为计算机科学与技术专业的核心课程实验,计算机网络实验面临教学内容相对滞后、实验平台单一、课程评价体系不完善等问题。以安徽理工大学计算机科学与工程学院开设的计算机网络实验课程为研究对象,立足教学一线实践,探索并构建了一个以能力培养为导向、虚实结合的实验平台为支撑、多元化评价为保障的实验教学体系。从模块化重构实验内容、建设软硬件融合实验平台、创新探索教学方法、搭建全过程动态评价体系四个方面对实验教学体系进行系统性的设计与构建。通过分析发现,改革方案显著提高了学生的实验参与度、动手操作能力及综合素养,也提升了教师的教学积极性和课程建设水平。 展开更多
关键词 “四新”教育 计算机网络 实验教学 虚拟仿真 教学改革
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虚拟水池网-SWMM耦合的城市洪涝高效模拟方法 认领 引用
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作者 黄源 周俊 +2 位作者 郑飞飞 熊俊熠 张钊 《水科学进展》 EI CAS CSCD 北大核心 2026年第2期349-361,共13页
针对城市洪涝模拟中计算效率与模拟精度难以兼顾的问题,提出一种基于虚拟水池网与SWMM耦合的新方法(StoSWMM)。该方法在SWMM框架内以子汇水区为单位构建虚拟水池网络,利用堰结构实现地表及地表-管网之间的双向水量交换,并基于虚拟水池... 针对城市洪涝模拟中计算效率与模拟精度难以兼顾的问题,提出一种基于虚拟水池网与SWMM耦合的新方法(StoSWMM)。该方法在SWMM框架内以子汇水区为单位构建虚拟水池网络,利用堰结构实现地表及地表-管网之间的双向水量交换,并基于虚拟水池水位与DEM高程差快速推算地表积水水深,实现洪涝全过程模拟。以河海大学江宁校区为研究区,将StoSWMM与二维水动力模型(2DHM)及基于检查井溢流的耦合水文水动力模型(CHHM)进行对比分析。结果显示,在本研究区与设定降雨情景下,StoSWMM在地表淹没范围、最大积水深度及积水演变过程的整体刻画方面与2DHM表现出较好的一致性;在最大水深超过0.3 m的区域,其空间相关系数为0.86~0.93,而CHHM为0.07~0.30,体现了不同模型在地表积水刻画机制和空间概化方式上的差异。在同等硬件条件下,StoSWMM可实现秒级运算,耗时约为CHHM的1/40、2DHM的1/300。该方法完全依托开源SWMM平台,在保持物理一致性的同时具备较高的计算效率,可为城市洪涝快速模拟与情景分析提供轻量化建模途径。 展开更多
关键词 洪涝模拟 城市洪涝模型 SWMM 虚拟水池网 计算效率
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基于空洞卷积神经网络的虚拟机工作负载预测算法 认领 引用
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作者 刘皓宇 田乐 郭茂祖 《科学技术与工程》 EI 北大核心 2026年第3期1128-1134,共7页
云计算系统需要进行准确的主动式资源分配以实现高质量的云服务和高效的云资源利用,而恰当的主动式资源分配需要对工作负载进行准确的预测。现有的很多适用于云计算系统的工作负载预测方法要么预测准确性有限,要么因开销过大而缺乏实用... 云计算系统需要进行准确的主动式资源分配以实现高质量的云服务和高效的云资源利用,而恰当的主动式资源分配需要对工作负载进行准确的预测。现有的很多适用于云计算系统的工作负载预测方法要么预测准确性有限,要么因开销过大而缺乏实用性。针对上述问题提出了基于空洞卷积神经网络的虚拟机工作负载预测算法(virtual machine workload prediction algorithm based on dilated convolutional neural network,VMWPD),该算法采用了基于空洞卷积神经网络的预测模型,应用了预测模型预测工作负载的变化量而不是直接预测工作负载的机制,并拥有实时预测和实时训练的能力,在预测准确度和开销之间取得了较好的平衡。评估实验结果表明,VMWPD相较于基于长短时记忆模型(long short-term memory,LSTM)的工作负载预测算法准确度提高了32.45%,且时间开销降低了45.10%。可见,本文方法在保证一定精度的情况下能大幅降低开销。 展开更多
关键词 负载预测 云计算 虚拟机 神经网络 时间序列预测 预测方法 数据分析 资源管理
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基于VNC的远程实验室 认领 引用 被引量：1
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作者 李岚 潘志安 魏华 《信息通信》 2010年第5期54-55,共2页
设计并实现了一种基于虚拟网络计算机(Virtual Network Computing,VNC)的远程实验室的建设方案。通过远程实验室的建设,使校内优质的教学资源实现了共享,在让更多学生受益的同时,探索出一条网络实验教学的新模式。
关键词 虚拟网络计算(VNC) 远程实验室
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基于生成对抗网络的服装虚拟试穿与个性化推荐系统 认领 引用
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作者 袁国朝 《西部皮革》 2026年第10期26-29,共4页
构建改进型条件生成对抗网络,引入深度图估计与多头注意力机制,将长短期记忆网络与视觉感知特征结合,设计个性化推荐模块,以用户行为序列和服装视觉特征进行推荐决策。虚拟试穿模块生成图像的峰值信噪比(PSNR)为38.62 dB,结构相似性(SS... 构建改进型条件生成对抗网络,引入深度图估计与多头注意力机制,将长短期记忆网络与视觉感知特征结合,设计个性化推荐模块,以用户行为序列和服装视觉特征进行推荐决策。虚拟试穿模块生成图像的峰值信噪比(PSNR)为38.62 dB,结构相似性(SSIM)为0.923,Fréchet起始距离(FID)为18.73,均优于VITON-HD、CAT-VTON、LEFFA和MG-VTON四种经典模型。个性化推荐模块的精确率(Precision@10)为87.5%,召回率(Recall@10)为79.3%。系统实现了虚拟试穿与个性化推荐的协同,为服装电商数字化转型提供了技术基础。 展开更多
关键词 生成对抗网络 虚拟试穿 个性化推荐 计算机视觉 服装电商
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Mobile Fog Computing by Using SDN/NFV on 5G Edge Nodes 认领 引用 被引量：4
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作者 G.R.Sreekanth S.Ahmed Najat Ahmed +3 位作者 Marko Sarac Ivana Strumberger Nebojsa Bacanin Miodrag Zivkovic 《Computer Systems Science & Engineering》 SCIE EI 2022年第5期751-765,共15页
Abstract:Fog computing provides quality of service for cloud infrastructure.As the data computation intensifies,edge computing becomes difficult.Therefore,mobile fog computing is used for reducing traffic and the time... Abstract:Fog computing provides quality of service for cloud infrastructure.As the data computation intensifies,edge computing becomes difficult.Therefore,mobile fog computing is used for reducing traffic and the time for data computation in the network.In previous studies,software-defined networking(SDN)and network functions virtualization(NFV)were used separately in edge computing.Current industrial and academic research is tackling to integrate SDN and NFV in different environments to address the challenges in performance,reliability,and scalability.SDN/NFV is still in development.The traditional Internet of things(IoT)data analysis system is only based on a linear and time-variant system that needs an IoT data system with a high-precision model.This paper proposes a combined architecture of SDN and NFV on an edge node server for IoT devices to reduce the computational complexity in cloud-based fog computing.SDN provides a generalization structure of the forwarding plane,which is separated from the control plane.Meanwhile,NFV concentrates on virtualization by combining the forwarding model with virtual network functions(VNFs)as a single or chain of VNFs,which leads to interoperability and consistency.The orchestrator layer in the proposed software-defined NFV is responsible for handling real-time tasks by using an edge node server through the SDN controller via four actions:task creation,modification,operation,and completion.Our proposed architecture is simulated on the EstiNet simulator,and total time delay,reliability,and satisfaction are used as evaluation parameters.The simulation results are compared with the results of existing architectures,such as software-defined unified virtual monitoring function and ASTP,to analyze the performance of the proposed architecture.The analysis results indicate that our proposed architecture achieves better performance in terms of total time delay(1800 s for 200 IoT devices),reliability(90%),and satisfaction(90%). 展开更多
关键词 Mobile fog computing edge computing edge node IoT softwaredefined networking network functions virtualization orchestrator
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面向数字创意产业的ANN-SNN混合神经网络架构研究 认领 引用
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作者 沈悦 《佛山科学技术学院学报（自然科学版）》 CAS 2026年第1期80-86,共7页
针对传统神经网络在处理大规模数据时的计算瓶颈和能效低的问题,提出了一种人工神经网络(ANN)与脉冲神经网络(SNN)深度融合的混合神经网络架构,该架构提升了虚拟现实(VR)和动漫创作的交互性、智能化程度和整体效率。引入了动态权重分配... 针对传统神经网络在处理大规模数据时的计算瓶颈和能效低的问题,提出了一种人工神经网络(ANN)与脉冲神经网络(SNN)深度融合的混合神经网络架构,该架构提升了虚拟现实(VR)和动漫创作的交互性、智能化程度和整体效率。引入了动态权重分配机制,利用任务感知的α和β系数动态调整ANN与SNN的输出贡献,以适应多模态数据的实时交互需求。同时,设计分层融合策略,在核心网络层实现时空特征的高效耦合,解决了传统模型在动态场景中的响应延迟问题。实验结果表明:ANN-SNN融合架构在多个维度上优于传统ANN模型和SNN模型。 展开更多
关键词 混合神经网络 虚拟现实技术 动漫设计 用户体验 计算效能
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利用VNC搭建远程实验室 认领 引用
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作者 胡昌杰 李岚 《电脑知识与技术》 2010年第3期1739-1740,共2页
分析了远程控制机制,针对远程实验室的搭建,设计并实现了一种基于虚拟网络计算（Virtual Network Computing,VNC）的远程实验室的解决方案。重点阐述了远程实验室架构的设计理念和关键技术,并对关键技术进行了步骤描述。
关键词 远程控制 虚拟网络计算(VNC) 远程实验室
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云计算技术在广播电视通信网络安全传输控制中的应用 认领 引用
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作者 王立轩 《电视电声科学与技术》 2026年第4期188-190,共3页
针对广播电视通信网络安全传输控制对弹性算力与动态资源配置的迫切需求,设计一种基于分布式云节点的安全传输控制架构,并分别建立传输控制综合评价模型与云端资源动态调度优化模型,在此基础上对虚拟化传输通道隔离加密及云端动态负载... 针对广播电视通信网络安全传输控制对弹性算力与动态资源配置的迫切需求,设计一种基于分布式云节点的安全传输控制架构,并分别建立传输控制综合评价模型与云端资源动态调度优化模型,在此基础上对虚拟化传输通道隔离加密及云端动态负载均衡两项关键技术的实施过程开展详细阐述。以直播传输与多通道并发传输两类工程场景为对象开展对比测试,测试结果验证了所述方案的工程可行性。 展开更多
关键词 云计算技术 广播电视通信网络 安全传输控制 虚拟化传输通道 动态负载均衡
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基于云计算的通信网络资源调度技术研究 认领 引用
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作者 廖华 杨忠敏 《通信电源技术》 2026年第14期137-139,共3页
针对传统通信网络资源调度模式效率低、适配性弱等问题,依托云计算技术构建4层协同调度架构,研究资源状态感知、智能混合调度算法、动态资源分配及闭环优化等关键技术,划分业务优先级完成资源合理配置,并搭建实验平台开展性能对比测试... 针对传统通信网络资源调度模式效率低、适配性弱等问题,依托云计算技术构建4层协同调度架构,研究资源状态感知、智能混合调度算法、动态资源分配及闭环优化等关键技术,划分业务优先级完成资源合理配置,并搭建实验平台开展性能对比测试。结果表明,该技术可显著提高网络资源利用率,降低业务传输时延与丢包率,兼顾各类业务调度公平性,能够有效满足5G及物联网场景下多元化通信业务运行需求。 展开更多
关键词 云计算 通信网络 资源调度 虚拟化 负载均衡
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