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Gaviss : Boosting the Performance of GPU-Accelerated NFV Systems via Data Sharing

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2022年第12期33卷 4472-4483页

作者： Guo, Liangchen Zhang, Kai Wang, X. Sean Fudan Univ Sch Comp Sci & Technol Shanghai 200437 Peoples R China

GPUs have demonstrated the capability of significantly improving the performance of network functions (NF). In an network function virtualization (NFV) system, multiple NFs form a service chain to provide services. However, NFs in state-of-the-art GPU-accelerated NFV systems still utilize a GPU independently where each NF needs to transfer data to the GPU memory for acceleration. As a result, a packet might be transferred into the GPU memory by each NF when it passes through the service chain. We find these expensive and repetitive transfers are the main factor that limits the overall performance of an NFV system. We propose Gaviss, a GPU-accelerated NFV system with effective data sharing. By sharing packets in the GPU memory among network functions, a packet needs to be transferred to the GPU only once, eliminating the performance overhead caused by repetitive transfers. Extensive experimental results show that Gaviss can improve the overall throughput by 2.6-13.2x and reduce the latency by up to 37.9%, when compared with state-of-the-art approaches. Moreover, Gaviss also demonstrates up to 2.5x higher price-performance ratio than CPU-based implementations, making GPUs competitive for building NFV systems.

关键词： Graphics processing units Data transfer Noise measurement Synchronization Kernel Throughput Logic gates Communications technology computer networks network function virtualization

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Scalable and Flexible Traffic Steering for Service function Chains

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2022年第3期19卷 2048-2062页

作者： Chen, Ruixin Zhao, Jin Fudan Univ Sch Comp Sci Shanghai 200438 Peoples R China Fudan Univ Shanghai Key Lab Intelligent Informat Proc Shanghai 200438 Peoples R China

network function virtualization (NFV) has inspired numerous orchestration algorithms to decide Virtualized network function (VNF) placement and routing paths for service requests with Service function Chain (SFC) demands. With different optimization goals, these algorithms may select various routing paths for request flows. Nevertheless, existing traffic steering solutions either fail to fully support NFV Orchestrator (NFVO) in path selection, or result in low scalability in the underlay Software Defined network (SDN). In this paper, we propose STAR to tackle both problems simultaneously. STAR divides the entire routing path for SFC request into several path segments, then performs Output-Port-based, Default-Path-based or RSP-ID-based traffic steering on each path segment. With the idea of path division and these traffic steering mechanisms, STAR achieves flexible traffic steering along any paths selected by NFVO and enables different Rendered Service Paths (RSPs) with the same path segments to share the same forwarding rules. In this way, STAR ensures the correct enforcement of path selection decisions from NFVO and significantly reduces forwarding rule consumption and control overhead. We evaluate STAR with the experiments on a real testbed and large-scale simulations. The results show that our framework is scalable in the SDN data plane and control plane (e.g., reducing rules in hardware switches by more than 70% compared with NSH-based solutions) while retaining the flexibility of steering traffic along any SFC routing paths to provide full support for path decision enforcement (e.g., achieving the highest path decision enforcement ratio in 11 of the 12 cases) with acceptable overhead.

关键词： Routing Switches Scalability Noise measurement Hardware Firewalls (computing) Software Service function chain network function virtualization traffic steering

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Energy Aware Fuzzy Approach for VNF Placement and Consolidation in Cloud Data Centers

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JOURNAL OF network AND SYSTEMS MANAGEMENT 2022年第3期30卷 1-29页

作者： Khemili, Wided Hajlaoui, Jalel Eddine Omri, Mohamed Nazih Univ Sousse Higher Inst Comp Sci & Commun Technol MARS Res Lab Sousse Tunisia Univ Sousse Natl Sch Engineers Sousse MARS Res Lab Sousse Tunisia

Virtual network function (VNF) is one of the pillars of a Cloud network that separates network functions and their dedicated hardware devices, such as routers, firewalls, and load balancers, to host their services on virtual machines. The VNF is responsible for network services that run on virtual machines and can connect each of them alone or organize themselves into a single enclosure to use all the resources available in that enclosure. This flexibility allows physical and virtual resources to be used in a way that ensures control over power consumption, balance in resource use, and minimizing costs and latency. In order to consolidate VNF groups into a minimum number of virtual machine (VM) with estimation of the association relation to a measure of confidence under the context of possibility theory, we propose a new Fuzzy-FCA approach for VNF placement based on formal concept analysis (FCA) and fuzzy logic in mixed environment based on cloud data centers and Multiple access edge computing (MEC) architecture. Thus, the inclusion of this architecture in the cloud environment ensures the distribution of compute resources to the end user in order to reduce end-to-end latency. To confirm the effectiveness of our solution, we compared it to one of the best algorithms studied in the literature, namely the MultiSwarm algorithm. The results of the series of experiments carried out show the feasibility and efficiency of our algorithm. Indeed, the harvested results confirm the capability of maximizing and balancing the use of resources, of minimizing the latency and the cost of energy consumption. The performance of our solution in terms of average latency represents 16%, a slight increase compared to MultiSwarm, and an average gain, of 49% in run time, compared to the same algorithm.

关键词： Cloud data centers Placement Consolidation Multiple access edge computing network function virtualization Formal concept analysis

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NURPS: NUMA- and Reliability-aware Parallelized SFC Deployment in Multi-Core Servers 17

NURPS: NUMA- and Reliability-aware Parallelized SFC Deployme...

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17th International Conference on COMmunication Systems and networkS, COMSNETS 2025

作者： Sameer, Shaik Chintapalli, Venkatarami Reddy National Institute of Technology Kerala Calicut India

ISBN: (纸本)9798331531195

network function virtualization (NFV) leverages Virtualized network functions (VNFs) to overcome the limitations of traditional middleboxes by using standard hardware to create Service function Chains (SFCs) that deliver specific services. However, virtualization overhead and SFC length can contribute to increased end-to-end delay. To address this, Paral-lelized SFC (PSFC) enables the simultaneous execution of identical packets by multiple VNFs, significantly reducing delay. Most existing SFC placement approaches assume uniform treatment of all CPU cores in multi-core NFV servers, overlooking the impact of Non-Uniform Memory Access (NUMA) architecture. Studies have shown that arbitrary VNF placement can degrade SFC performance due to resource contention within a NUMA node - specifically in the Last Level Cache (LLC) and Memory Bandwidth (MB) - and between NUMA nodes, particularly in Quick Path Interconnect (QPI) bandwidth. This paper presents NURPS, a NUMA-aware PSFC placement strategy that deploys VNFs by allocating critical resources, such as LLC and MB, across NUMA nodes to maximize performance while minimizing server usage. Furthermore, NURPS incorporates both software and hardware reliability into the VNF deployment process, ensuring stable performance under varying operational conditions. Extensive simulations demonstrate that NURPS effectively reduces the number of servers required for PSFC deployment while maintaining high reliability. © 2025 IEEE.

关键词： network function virtualization

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Chain Segment Protection for Dependence-aware Service function Chain in NFV 7

Chain Segment Protection for Dependence-aware Service Functi...

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7th World Conference on Computing and Communication Technologies, WCCCT 2024

作者： Peng, Chengzong Bai, Yang Yang, Siqi Zheng, Danyang Cao, Xiaojun Chengdu China Southwest Jiaotong University School of Computing and Artificial Intelligence Chengdu China Georgia State University Department of Computer Science United States

ISBN: (纸本)9798350372328

network services can be delivered through a service function chain (SFC) for reliability-sensitive applications. Traditional SFC protection can be employed by providing a node-link-disjoint backup path to avoid SFC disruption. However, such a backup path may not exist in the network with limited resources. In this work, we propose a chain segment protection, which can effectively protect an SFC using several backup chain segments when a node-link-disjoint backup path is not available. We investigate how to jointly embed and provide chain segment protection while reducing the backup bandwidth resources. We define this problem as SFC failure with chain segment protection (SFCF-CSP), which is proved to be NP-hard. To address SFCF-CSP, we propose an efficient heuristic algorithms called backup chain-segment embedding and protection (BCEP). The simulation results show that the proposed algorithm outperforms the approaches that are directly extended from the existing work. © 2024 IEEE.

关键词： network function virtualization

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Dynamic Service function Chain Deployment in NFV-enabled Offshore Edge Computing networks 14

Dynamic Service Function Chain Deployment in NFV-enabled Off...

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14th International Conference on Information Science and Technology, ICIST 2024

作者： Han, Yongchun Lin, Bin Zhang, Chaoyue Wang, Qiaodan Information Science and Technology College Dalian Maritime University Dalian China

ISBN: (纸本)9798350353334

network function virtualization (NFV) has gained significant attention as an important paradigm in the network service provisioning. In the NFV environment, network services are provided flexibly by deploying service function chains (SFCs) dynamically, which consist of multiple virtual network functions (VNFs) arranged in predefined order. In this paper, we formulate the dynamic SFC deployment optimization (DSDO) problem in the NFV-enabled offshore edge computing network, by jointly optimizing VNF deployment and routing to maximize the service acceptance rate. An SFC deployment scheme, named betweenness centrality and resource availability based dynamic SFC deployment (BR-DSD) scheme, is proposed to solve the optimization problem. The proposed BR-DSD scheme aims to allocate resources for SFCs by considering both network resources availability and network betweenness centrality. Simulation results demonstrate that the proposed BR-DSD scheme outperforms baseline schemes in terms of service acceptance rate. © 2024 IEEE.

关键词： network function virtualization

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SA-PSO Approach for Optimizing QoS Management in SDN Service Chains

SA-PSO Approach for Optimizing QoS Management in SDN Service...

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2024 IEEE Cyber Science and Technology Congress

作者： Ji, Wen Lin, Chenhan Liu, Jiang Xu, Hongyang Xu, Liangjie Hu, Jun State Grid Fujian Elect Power Co Ltd Informat & Commun Branch Fuzhou Peoples R China Anhui Jiyuan Software Co Ltd Syst Integrat Business Unit Hefei Peoples R China

ISBN: (纸本)9798331532109;9798331532093

In recent years, the development of software-defined networking (SDN) and network function virtualization (NFV) has provided greater flexibility and programmability for network services. As a novel network architecture, Service function Chaining (SFC) offers operators more possibilities in deploying and managing network service functions. However, current research often overlooks user Quality of Service (QoS) requirements, focusing primarily on operator interests. This paper addresses this gap by proposing a novel approach that integrates multidimensional QoS parameters and combines Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithms to optimize QoS service management in SDN/NFV environments. Specifically, we devise a hybrid optimization strategy based on SA and PSO to achieve efficient resource allocation and service chain scheduling, aiming to enhance the overall QoS experience for users. Experimental results demonstrate significant improvements in network service delivery efficiency and user satisfaction, validating the effectiveness and practicality of the proposed approach.

关键词： Quality of Service Software-defined networking network function virtualization Service function Chaining Simulated Annealing algorithm Particle Swarm Optimization algorithm

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Cost-Aware, Profiling-based Resource Configuration for Virtual network function Forwarding Graphs 28

Cost-Aware, Profiling-based Resource Configuration for Virtu...

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28th Conference on Innovation in Clouds, Internet and networks, ICIN 2025

作者： Daemi, Nafiseh Ebrahimzadeh, Amin Mouradian, Carla Wuhib, Fetahi Glitho, Roch H. CIISE Concordia University MontréalQC Canada Ericsson Research MontréalQC Canada

ISBN: (纸本)9798331542399

network function virtualization (NFV) enables Virtual network functions (VNFs) to run on shared physical infrastructure, offering flexible resource management. A key challenge in NFV environments is determining the optimal resource configuration for VNFs, particularly in a VNF-Forwarding Graph (VNF-FG) where dependencies between VNFs complicate the process. This paper introduces a Cost-Aware Profiling-based Resource Configuration (CA-PRC) algorithm, which dynamically adjusts the resource configurations to minimize the total allocated CPU while achieving performance targets specified in the Service Level Agreements (SLAs). The proposed CA-PRC algorithm incrementally generates performance profiles for VNFs and balances the trade-off between CPU allocation and profiling cost, thus reducing the need for an exhaustive profiling. Our evaluations demonstrate that the proposed algorithm significantly outperforms the Uniform Random Selection (URS) and Weighted Random VNF Selection (WRVS) in terms of the number of required profiling rounds and total allocated CPU. © 2025 IEEE.

关键词： network function virtualization

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A reinforcement learning-based approach for availability-aware service function chain placement in large-scale networks

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2022年 136卷 93-109页

作者： Santos, Guto Leoni Endo, Patricia Takako Lynn, Theo Sadok, Djamel Kelner, Judith Univ Fed Pernambuco Recife PE Brazil Univ Pernambuco Recife PE Brazil Dublin City Univ Dublin Ireland

By decoupling network service functions from custom-built hardware, network function virtualization is transforming network service provisioning, making large scale telecommunications more flexible, scalable, and agile. Service function chaining often requires network traffic to flow through a specific sequence of virtual network functions (VNFs) to comply with network policies. The dependencies between VNFs in such a chain can significantly and negatively impact the availability of an end-to-end service function chain (SFC) when one or more VNFs malfunction or fail. While redundancy strategies can be used to reduce the impact of such failure, this can increase operational expenditure and energy consumption. In this paper, we propose a solution for SFC placement based on reinforcement learning (RL) taking into account SFC availability, operational costs, and energy consumption. The Cand-RL algorithm uses RL based on proximal policy optimization (PPO) to select the suitable candidate node and define the redundancy strategy to meet availability requirements. We compare Cand-RL against two greedy algorithms in a variety of simulated scenarios. The results show that the Cand-RL outperforms the greedy algorithms, achieving a higher acceptance rate and a good balance between availability, placement cost, and energy consumption. (C) 2022 Elsevier B.V. All rights reserved.

关键词： Reinforcement learning Service function chain Proximal policy optimization Virtual network function network function virtualization NVF placement

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Distributed Ledger Technologies for network Slicing: A Survey

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IEEE ACCESS 2022年 10卷 19412-19442页

作者： Javed, Farhana Antevski, Kiril Mangues-Bafalluy, Josep Giupponi, Lorenza Bernardos, Carlos J. Ctr Tecnol Telecomunicac Catalunya CTTC CERCA Barcelona 08860 Spain Univ Carlos III Madrid UC3M Telemat Engn Dept Getafe 28911 Spain

network slicing is one of the fundamental tenets of Fifth Generation (5G)/Sixth Generation (6G) networks. Deploying slices requires end-to-end (E2E) control of services and the underlying resources in a network substrate featuring an increasing number of stakeholders. Beyond the technical difficulties this entails, there is a long list of administrative negotiations among parties that do not necessarily trust each other, which often requires costly manual processes, including the legal construction of neutral entities. In this context, Blockchain comes to the rescue by bringing its decentralized yet immutable and auditable lemdger, which has a high potential in the telco arena. In this sense, it may help to automate some of the above costly processes. There have been some proposals in this direction that are applied to various problems among different stakeholders. This paper aims at structuring this field of knowledge by, first, providing introductions to network slicing and blockchain technologies. Then, state-of-the-art is presented through a global architecture that aggregates the various proposals into a coherent whole while showing the motivation behind applying Blockchain and smart contracts to network slicing. And finally, some limitations of current work, future challenges and research directions are also presented.

关键词： Blockchains network slicing Distributed ledger 5G mobile communication network function virtualization Stakeholders Next generation networking Distributed ledger technologies blockchain network slicing beyond 5G 6G smart contracts

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