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检索条件"主题词=Network Function Virtualization"

共 3191 条记录，以下是931-940 订阅

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HA/TCP: A Reliable and Scalable Framework for TCP network functions

HA/TCP: A Reliable and Scalable Framework for TCP Network Fu...

引用

22nd USENIX Symposium on networked Systems Design and Implementation, NSDI 2025

作者： Gu, Haoyu Mashtizadeh, Ali José Wong, Bernard University of Waterloo Canada

ISBN: (纸本)9781939133465

Layer 7 network functions (NFs) are a critical piece of modern network infrastructure. As a result, the scalability and reliability of these NFs are important but challenging because of the complexity of layer 7 NFs. This paper presents HA/TCP, a framework that enables migration and failover of layer 7 NFs. HA/TCP uses a novel replication mechanism to synchronize the state between replicas with low overhead, enabling seamless migration and failover of TCP connections. HA/TCP encapsulates the implementation details into our replicated socket interface to allow developers to easily add high availability to their layer 7 NFs such as WAN accelerators, load balancers, and proxies. Our benchmarks show that HA/TCP provides reliability for a 100 Gbps NF with as little as 0.2% decrease in client throughput. HA/TCP transparently migrates a connection between replicas in 38 µs, including the network latency. We provide reliability to a SOCKS proxy and a WAN accelerator with less than 2% decrease in throughput and a modest increase in CPU usage. © 2025 by The USENIX Association All Rights Reserved.

关键词： network function virtualization

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OOTDiffusion: Outfitting Fusion Based Latent Diffusion for Controllable Virtual Try-On 39

OOTDiffusion: Outfitting Fusion Based Latent Diffusion for C...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Xu, Yuhao Gu, Tao Chen, Weifeng Chen, Arlene Xiao-i Research China

ISBN: (纸本)157735897X

We present OOTDiffusion, a novel network architecture for realistic and controllable image-based virtual try-on (VTON). We leverage the power of pretrained latent diffusion models, designing an outfitting UNet to learn the detailed garment features. Without a redundant warping process, the garment features are precisely aligned with the target human body via the proposed outfitting fusion in the self-attention layers of the denoising UNet. In order to further enhance the controllability, we introduce outfitting dropout to the training process, which enables us to adjust the strength of the garment features through classifier-free guidance. Our comprehensive experiments on the VITON-HD and Dress Code datasets demonstrate that OOTDiffusion efficiently generates high-quality try-on results for arbitrary human and garment images, which outperforms other VTON methods in both realism and controllability, indicating a breakthrough in virtual try-on. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： network function virtualization

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FLEXFL: Flexible Federated Learning for Customized network Architectures in 6G

FLEXFL: Flexible Federated Learning for Customized Network A...

引用

2025 IEEE Wireless Communications and networking Conference, WCNC 2025

作者： Khowaja, Sunder Ali Lee, Ik Hyun Khuwaja, Parus Bhatti, Naveed Anwar Singh, Keshav Dev, Kapal Dublin City University Ireland Tech University of Korea Siheung-Si Iklab Inc. Seoul Korea Republic of Institute of Business Administration University of Sindh Pakistan Lums Pakistan National Sun Yat-sen University Taiwan Munster Technological University Ireland

ISBN: (纸本)9798350368369

With the continuous and fast-changing land-scape in communication networks and artificial intelligence (AI), the researchers are interested in expedited standardization and realization of 6G networks. Federated learning (FL) is one of the paradigms that allows the 6G networks to support a diverse range of devices. Very few studies address the problem of flexibility and heterogeneity for AI network architectures in FL paradigm, that could be a potential key changer for standardization and realization of 6G networks. However, they either consider width-only or depth-only to provide flexibility support. Furthermore, the existing studies do not address the problem of weight scale variation while performing the global model aggregation at the server side. In this regard, we propose flexible federated learning (FLEXFL) for the support of heterogeneous AI network architectures in 6G communication systems. The proposed network not only considers the width but also the depth of the network architecture to make it compliant with the global model aggregation. We also address weight scale variation (WSV) while updating the global model with weight normalization, which is one of the problems associated with existing studies. We perform experimental analysis on two publicly available datasets and a few network architectures to show the efficacy of the proposed approach. The results reveal that the FLEXFL outperforms existing state-of-the-art works in both the IID and non-IID settings, accordingly. © 2025 IEEE.

关键词： network function virtualization

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ParaDSP: Parallelism-aware Dynamic SFC Placement in NFV-based networks

ParaDSP: Parallelism-aware Dynamic SFC Placement in NFV-base...

引用

International Communication Systems and networks and Workshops, COMSNETS

作者： Venkatarami Reddy Chintapalli Rajat Partani Balaprakasa Rao Killi Bheemarjuna Reddy Tamma National Institute of Technology Calicut India National Institute of Technology India National Institute of Technology Warangal India Indian Institute of Technology Hyderabad India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

In the context of network function virtualization (NFV), the shift from hardware-based middleboxes to software-based Virtual network functions (VNFs) on commodity servers promises cost savings and operational flexibility. However, this transition introduces challenges, particularly the increased end-to-end (E2E) delay of Service function Chains (SFCs) due to VNF processing overhead from the virtualization layer. The E2E delay further scales with the length of the SFC, posing a critical issue for latency-sensitive applications. To address this, parallelized SFCs (PSFCs) have been proposed, leveraging the parallel execution of VNFs to reduce E2E delay. In this paper, we introduce a novel PSFC deployment scheme aimed at enhancing network performance by effectively utilizing vertical scalability, which involves using idle resources within a server to adapt to fluctuating traffic. A mathematical model is developed for PSFC deployment that optimizes resource utilization, considering peak traffic rates of PSFCs, and manages accepted SFC requests while accounting for virtualization overhead. We also propose a heuristic algorithm paraDSP, which increases vertical scalability and ensures E2E delay constraints of PSFCs. Simulation results demonstrate that the proposed scheme significantly improves performance in terms PSFC acceptance rate and packet loss compared to state-of-the-art solutions.

关键词： Service function chaining Scalability Simulation Packet loss Middleboxes Delays network function virtualization Servers Resource management virtualization

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Mitigating Scalability Walls of RDMA-based Container networks

Mitigating Scalability Walls of RDMA-based Container Network...

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22nd USENIX Symposium on networked Systems Design and Implementation, NSDI 2025

作者： Liu, Wei Qian, Kun Li, Zhenhua Qian, Feng Xu, Tianyin Liu, Yunhao Guan, Yu Zhu, Shuhong Xu, Hongfei Xi, Lanlan Qin, Chao Zhai, Ennan Tsinghua University China Alibaba Cloud China University of Southern California United States UIUC United States

ISBN: (纸本)9781939133465

As a state-of-the-art technique, RDMA-offloaded container networks (RCNs) can provide high-performance data communications among containers. Nevertheless, this seems to be subject to the RCN scale-when there are millions of containers simultaneously running in a data center, the performance decreases sharply and unexpectedly. In particular, we observe that most performance issues are related to RDMA NICs (RNICs), whose design and implementation defects might constitute the "scalability wall" of the RCN. To validate the conjecture, however, we are challenged by the limited visibility into the internals of today's RNICs. To address the dilemma, a more pragmatic approach is to infer the most likely causes of the performance issues according to the common abstractions of an RNIC's components and functionalities. Specifically, we conduct combinatorial causal testing to efficiently reason about an RNIC's architecture model, effectively approximate its performance model, and thereby proactively optimize the NF (network function) offloading schedule. We embody the design into a practical system dubbed ScalaCN. Evaluation on production workloads shows that the end-to-end network bandwidth increases by 1.4× and the packet forwarding latency decreases by 31%, after resolving 82% of the causes inferred by ScalaCN. We report the performance issues of RNICs and the most likely causes to relevant vendors, all of which have been encouragingly confirmed;we are now closely working with the vendors to fix them. © 2025 by The USENIX Association All Rights Reserved.

关键词： network function virtualization

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Tiny objects classification on remote sensing image by using multi-scale crop

Tiny objects classification on remote sensing image by using...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Su, Rou-Ying Lee, Pei-Jun The Electronic and Computer Engineering Department National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (纸本)9798331521165

Classifying tiny objects in remote sensing images (e.g., a 20x20 pixels target within a resolution 1000x1000 image) is a significant challenge. This paper adopts a fused FPN (Feature Pyramid network) to enhance the feature extraction capability for tiny objects. Additionally, the proposed multi-scale crop method can more effectively focus on the target objects. This network architecture improves overall accuracy by 14.4%. © 2025 IEEE.

关键词： network function virtualization

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Service function Chaining on SDN/NFV based programmable data plane

Service Function Chaining on SDN/NFV based programmable data...

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International Conference on Computing and networking Technology (ICCNT)

作者： Meignanamoorthi Dhanapani V. Vetriselvi Department of Computer Science and Engineering (DCSE) College of Engineering Guindy Anna university Chennai India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Software-Defined networking (SDN) and network function virtualization (NFV) are transforming next-generation networks. SDN’s data plane programmability unlocks new levels of network flexibility. NFV simplifies management of essential network functions like firewalls and intrusion detection systems. Service function Chaining (SFC) offers increased manageability by defining ordered sequences of these functions as virtual chains. However, enforcing SFC through traditional network switches is complex. This paper proposes a novel architecture that leverages the power of SDN and NFV for efficient SFC packet processing. By utilizing the programmability of modern switches, our design enforces SFC directly on the data plane. Experimental results demonstrate significant performance improvements in processing time compared to the widely used OpenVSwitch. This approach paves the way for high-performance and scalable SFC enforcement in next-generation networks.

关键词： Service function chaining Firewalls (computing) Intrusion detection Computer architecture network function virtualization Next generation networking

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Real-Time Monitoring of 5G networks: An NWDAF and ML Based KPI Prediction

Real-Time Monitoring of 5G Networks: An NWDAF and ML Based K...

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IEEE Conference on network Softwarization (NetSoft)

作者： Abebu Ademe Bayleyegn Zaloa Fernández Fabrizio Granelli Dept. of Information Engineering and Computer Science (DISI) Trento Italy Vicomtech Foundation Basque Research and Technology Alliance (BRTA) San Sebastián Spain

ISBN: (数字)9798350369588

ISBN: (纸本)9798350369595

The emergence of 5G networks plays a crucial role in satisfying the diverse demands of the rapidly evolving telecommunications market. The introduction of network function virtualization (NFV) and Software-Defined networks (SDN) offers significant networking advantages by transforming hardware-dependent network functions into programmable and cost-efficient Virtual network functions (VNFs). However, for effective monitoring strategies and enforcing Service Level Agreements (SLAs), these virtualized networks must be made visible (observable) to service providers or network operators. Extensive research has been undertaken to address monitoring and analytics challenges as networks transition to virtualized environments. This paper presents the development and evaluation of a real-time monitoring solution for 5G Service-Based Architecture (SBA) by leveraging a network Data Analytics function (NWDAF) developed by the authors. This solution allows and demonstrates real-time monitoring of 5G networks via a standardized interface. In addition, NWDAF is extended to utilize Machine Learning (ML) models to predict Key Performance Indicators (KPIs) related to network traffic, enhancing the overall network analytics capabilities. Furthermore, the collected metrics from the 5G core are pushed into a Prometheus database, with Grafana providing a visual analytics tool for assessing network performance.

关键词： 5G mobile communication Visual analytics Key performance indicator Telecommunication traffic Real-time systems network function virtualization Telecommunications

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Cross-Compartment Virtio-Loopback: A Bare-Metal virtualization Solution for the Edge

Cross-Compartment Virtio-Loopback: A Bare-Metal Virtualizati...

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International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC)

作者： Anna Panagopoulou Alvise Rigo Daniel Raho Virtual Open Systems SAS Grenoble France

ISBN: (数字)9798350373905

ISBN: (纸本)9798350373912

With the evolution of 5G technologies and beyond, paradigms like the Mobile Edge Computing (MEC) mandate the deployment of services at the edge of the network and close to the users. Contributing to further reducing the latency and improving network performance, these paradigms are essential constituents of a networked infrastructure supporting ultra-reliable and low-latency services, as in the case of the recently emerging intelligent transportation services (ITS). With MEC being coupled with network functions virtualization (NFV), these services are deployed upon the cellular V2X interface as Virtualized network functions (VNFs) across the various network domains, including the network edge. This paper proposes a virtualization solution suited for VNF deployments of these services at mixed-critical, embedded edge servers. The solution suggests that VNFs interfacing abstracted Virtio devices are hosted at individual and isolated bare-metal Operating Systems (OSes) or compartments, co-executing at the same hardware with different criticality. The current proof-of-concept targets ARMv8 embedded servers and introduces a split client-server Virtio design, extending an existing virtualization framework across bare-metal compartments. Finally, benchmarks on a virtualized embedded board show that the Cross-compartment Virtio-loopback design does not introduce extra overhead compared to the reference implementation.

关键词： Protocols Transportation Computer architecture Benchmark testing Hardware Real-time systems network function virtualization Servers virtualization Low latency communication

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SimV: A Self-extension Similarity Viterbi Algorithm for Service function Chain Deployment for Multi-access Edge Computing

SimV: A Self-extension Similarity Viterbi Algorithm for Serv...

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Wenqiang Deng School of Computer Science Guangzhou College of Applied Science and Technology Zhaoqing China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Advancements in Multi-access Edge Computing (MEC) and network function virtualization (NFV) offer a lot of potential for providing flexible and low-latency network services at the edge. In NFV, traditional middleboxes are transformed into Virtual network functions (VNFs), which are then combined into Service function Chains (SFCs) to deliver complex network services. However, the features of MEC hosts and VNFs, along with the heterogeneity of their resources, make it challenging to develop low-latency deployment solutions. In this paper, we formulate the problem of Service function Chain Deployments in Edge networks to minimize Latency under Heterogeneous conditions (SDELH). To address this problem, we designed a self-extension Similarity Viterbi algorithm (SimV), which contains three sub-algorithms. Firstly, a basic Viterbi algorithm is employed to find the delay-optimized SFC deployment path. Secondly, a similarity algorithm is designed to assess suitable hosts for each VNF to streamline the matching process and reduce the time complexity of the Viterbi algorithm. Lastly, a self-extension method is devised to broaden the solution space for enhancing the SFC acceptance rate. Extensive simulations are conducted. Based on the comparison simulation results, SimV significantly reduces decision time for deployment, and outperforms the compared algorithms in terms of latency, number of accepted requests, and scalability, with average improvements of 20.37%, 6.04%, and 14.49%, respectively.

关键词： Distributed processing Multi-access edge computing Viterbi algorithm Service function chaining Scalability Simulation Middleboxes network function virtualization Low latency communication Time complexity

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