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On Efficient Delay-Aware Multisource Multicasting in NFV-Enabled Softwarized networks

IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2022年第3期19卷 3371-3386页

作者： Ren, Cheng Chen, Xuxiang Xiang, Haiyun Wang, Yu Li, Yaxin Li, Hao Southwest Petr Univ Sch Elect Engn & Informat Chengdu 610500 Peoples R China Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 610056 Peoples R China Southwest Petr Univ Network & Informat Ctr Chengdu 610500 Peoples R China

To comply with security and performance policies, multicast communication requires inline service that chains an ordered sequence of virtualized network functions (VNFs) with an emerging paradigm of network function virtualization (NFV). As many-to-many multicast pattern is widely used especially in current MEC, multimedia and big data industries, in this paper we focus on multi-source NFV-enabled multicasting in software-defined networks (SDN). By jointly investigating VNF placement and multicast tree routing strategy, it is envisioned to construct service function tree with minimum network resource expenditure while yielding lower delay. We explore this problem in static and online scenarios individually. In static situation with a bunch of multicast requests to be served, a column generation based computing model is first formulated, based on which an approximation algorithm MDNM that leverages logic of Viterbi and puts emphasis on resource optimization and segmental delay satisfaction is developed. In online situation with a single incoming request, another ILP model to enhance VNF instance reuse is established. Then, SVM algorithm giving importance to source determination and VNF instance consolidation is designed to efficiently construct a service function tree with minimum resource usage and delay. Simulation results show that the gap between each of the two proposed algorithms and their respective ILP models is marginal, and both MDNM and SVM outperform the state-of-art work.

关键词： Delays Costs Routing Radio frequency Multicast communication Multicast algorithms Switches Multicast network function virtualization software-defined networks service function tree

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Delay-aware and Resource-efficient VNF placement in 6G Non-Terrestrial networks

Delay-aware and Resource-efficient VNF placement in 6G Non-T...

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IEEE Wireless Communications and networking Conference (WCNC)

作者： Yue, Yi Tang, Xiongyang Yang, Wencong Zhang, Xuebei Zhang, Zhiyan Gao, Chuyang Xu, Lexi China Unicom Res Inst Beijing Peoples R China Zhengzhou Univ Sch Elect Engn Zhengzhou Peoples R China Univ Bern Bern Switzerland

ISBN: (纸本)9781665491228

Virtual network function (VNF) placement in NTNs is challenging because Non-Terrestrial networks (NTNs), such as satellite networks, have limited resources regarding computational power and rate. However, existing solutions do not consider satellites' resource constraints and the bandwidth constraints of links, which are essential metrics for designing VNF placement strategies in NTNs. Utilizing network function virtualization (NFV) technology to deploy related network services on satellites in VNFs is a reasonable way. This paper focuses on delay-aware VNF placement in 6G NTNs to meet the ultra-low delay requirements of different applications. In addition, we also consider how to improve the resource utilization of servers to eliminate the resource bottlenecks of resource-constrained 6G NTN facilities. Then we formulate the VNF placement problem as a weighted graph-matching problem, aiming to maximize resource utilization. We propose the Linear Programming based algorithm and the Hungarian-based algorithm to solve the VNF placement problem. Evaluation results show that our proposed solutions outperform the benchmarks regarding resource utilization and execution time.

关键词： 6G Non-terrestrial networks network function virtualization Virtual network function Delay-aware Resource utilization

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Hybrid Testbed for Security Research in Software-Defined networks

Hybrid Testbed for Security Research in Software-Defined Net...

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4th IEEE Conference on network function virtualization / 9th Software Defined networks Conference (IEEE NFV-SDN)

作者： Windisch, Fritz Abedi, Kamyar Doan, Tung Strufe, Thorsten Nguyen, Giang T. Tech Univ Dresden Chair Privacy & Secur Dresden Germany KIT Chair IT Secur Munich Germany Tech Univ Dresden Hapt Commun Syst Dresden Germany Ctr Tactile Internet Human Loop CeTI Dresden Germany

ISBN: (纸本)9798350302547

Tele-operations require secure end-to-end network Slicing leveraging Software-Defined networking to meet the diverse requirements of multi-modal data streams. Research on network slicing needs tools to develop prototypes quickly that work on emulation and practical deployment. However, state-of-the-art tools focus only on emulation, needing more support for a mixed testbed, including hardware devices. We decouple the topology generating from the actual deployment on destination domains and apply a divide-and-conquer approach. The master coordinator generates an Intermediate Representation (IR) layer, a serialization of the topology. Via a toolchain, the worker coordinators at autonomous systems convert the IR into full or partial deployment scripts. The testbed introduces a marginal overhead by design, allowing for flexible deployment of complex topologies to study secure end-to-end network Slicing.

关键词： Secure network Slicing Software-Defined networks OpenFlow network function virtualization LXC

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Towards Practical Dynamic Trust Monitoring of Containerized Services in NFV Infrastructure

Towards Practical Dynamic Trust Monitoring of Containerized ...

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IEEE International Conference on Communications (IEEE ICC)

作者： De Riggi, Valeria Vogt, Raphael Kalinagac, Onur Gur, Gurkan Zurich Univ Appl Sci ZHAW Inst Appl Informat Technol InIT CH-8401 Winterthur Switzerland

ISBN: (纸本)9781538674628

Although network function virtualization (NFV) and containerized services embedded therein are an already active research field while becoming increasingly widespread in practice (e.g., 5G networks), the trust and security challenges still deserve more attention. To tackle relevant issues for this aspect, our work deals with the question of whether and how the issue of trust assessment can be addressed in such infrastructures. Different trust models are reviewed, and the trust attributes used in the literature are analysed and evaluated. These parameters are subsequently included in a trust calculation framework for their confidence analysis. Finally, a Dynamic Trust Monitoring (DTM) solution, namely MicroDTM, that supervises the trustworthiness of containerized services in an NFV infrastructure is proposed. By collecting and processing the trust parameters, a containerized service environment is evaluated according to trustworthiness for different scenarios. In addition to performance analysis, improvements and extensions necessary to use the system in a practical environment are identified.

关键词： network function virtualization

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Enhancing Virtualized network functions through Advanced Machine Learning for Efficient Resource Allocation and Dynamic Placement 21

Enhancing Virtualized Network Functions through Advanced Mac...

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2024 IEEE/ACS 21st International Conference on Computer Systems and Applications, AICCSA 2024

作者： Gadouh, Khaled Ahmed Sellami, Hend Koubaa The National School of Electronics and Telecommunication Sfax Tunisia

ISBN: (纸本)9798331518240

This paper addresses the challenges of network functions virtualization (NFV) with a specific focus on the optimization of Virtualized network functions (VNFs) through advanced machine learning techniques. As NFV evolves to support modern network demands, including the upcoming transition from 5G to 6G technologies, efficient resource allocation and dynamic VNF placement become crucial. Traditional methods often fail to meet these requirements due to their static nature and inability to adapt to changing network conditions dynamically. we introduce a comprehensive framework including the integration of multiple machine learning models (i.e., Random Forest, Decision Trees, SVR) combined into ensemble approach such as Linear regression to predict and optimize VNF performance dynamically. This scheme not only improves the reliability of resource placement, but also is conducive to realizing the automatic scalable VNF deployment for ZSM: Zero-Touch network and Service Management. Here, all of these highlight that the ensemble model is better than the individual predictive machine models in predicting/amodeling network conditions as well as adjusting resources efficiently. The proposed model achieves very good results, improving in all the relevant key performance metrics RMSE, R2 and Explained Variance), and thus demonstrating that machine learning can bring deep changes to NFV environments. Though the study demonstrates the potential amplitude of these models, it also reveals significant challenges in bringing them to deployment levels, in specific extreme MAPE (Mean Absolute Percentage Error) cases. As such it opens doors for more research and development into this area too This work aims to expand the horizon of intelligent network management through actionable knowledge and guides from machine learning on improving the effectiveness and efficiency of network services supporting further adaptive, user-oriented networking schemes. © 2024 IEEE.

关键词： network function virtualization

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Automatic Service Migration in a MEC-NFV Environment

Automatic Service Migration in a MEC-NFV Environment

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2024 IEEE Conference on network function virtualization and Software Defined networks, NFV-SDN 2024

作者： Pereira, Pedro Escaleira, Pedro Gomes, Diogo Aguiar, Rui Instituto de Telecomunicações University of Aveiro Aveiro Portugal

ISBN: (纸本)9798350380538

network functions virtualization (NFV) and Multi-access Edge Computing (MEC) represent significant advancements in the telecommunications industry, addressing critical issues related to cost, complexity, and service agility. In MEC, it is essential to ensure seamless service migration to guarantee the system’s optimal performance. Our proposed architecture, based on the European Telecommunications Standards Institute MEC-NFV framework, aims to enable automatic metrics-based service migration. Our mechanism allows the client to specify the conditions in which the application should be hosted. By monitoring the resource usage of the applications, the system can react accordingly by scheduling service migration operations. To verify the practical impact of our proposal, we implemented a Proof of Concept (PoC), which we made open-source. ©2024 IEEE.

关键词： network function virtualization

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Dynamic VNF Deployment and Resource Allocation in Mobile Edge Computing 22

Dynamic VNF Deployment and Resource Allocation in Mobile Edg...

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Zhai, Xiaolong He, Zhenli Xiao, Yuanfei Wu, Junjie Yu, Xuejie Yunnan University Yunnan Key Laboratory of Software Engineering Kunming China Yunnan University School of Software Kunming650504 China

ISBN: (纸本)9798331509712

The explosive growth of terminal devices at the network edge, coupled with advancements in communication technology, poses significant challenges to traditional cloud computing models. Despite Mobile Edge Computing (MEC) mitigating some issues by enabling real-time data processing closer to the source, it faces challenges with linear growth in computational resources insufficient to meet the exponential growth in service demand. Existing research utilizing Software-Defined networking (SDN), network functions virtualization (NFV), and Service function Chain (SFC) technologies has made progress but still faces critical issues, such as the inability to respond in real-time to dynamic demands and inefficiencies in resource management strategies. This paper addresses these challenges by optimizing Virtual network function (VNF) deployment strategies in MEC environments. We propose PPO-ERA, a novel algorithm leveraging deep reinforcement learning and the Karush-Kuhn-Tucker (KKT) method. This approach provides real-time, adaptive, and dynamic deployment policies for VNFs, significantly improving both the average response delay of tasks and resource utilization. Key contributions include rigorous SFC-based application modeling, dynamic VNF deployment algorithms, elastic resource allocation, uniform state representation, and extensive performance validation. These advancements enhance the adaptability, efficiency, and performance of VNF deployment strategies, addressing critical challenges in dynamic MEC environments. © 2024 IEEE.

关键词： network function virtualization

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SP-ADMM: a distributed optimization method of SFC placement for 5G-MEC networks 3

SP-ADMM: a distributed optimization method of SFC placement ...

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3rd International Conference on Algorithms, Microchips, and network Applications, AMNA 2024

作者： Zhang, Zhibo Wang, Huiqiang Niu, Shuangyue Lv, Hongwu College of Computer Science and Technology Harbin Engineering University Harbin China AVIC Chengdu Aircraft Design and Research Institute Chengdu China

ISBN: (纸本)9781510680098

Recently, the combination of a service function chain (SFC) with network function virtualization (NFV) and software-defined networking (SDN) has provided customers with flexible and efficient services. The emergence of multi-access edge computing (MEC) further enhances the level of service customization. However, achieving joint optimization of virtual network function (VNF) deployment and flow allocation in resource-constrained scenarios while meeting the diverse requirements of 5G verticals is challenging. Current research rarely addresses dedicated service provisioning for edge servers and considers the additional instantiation overhead introduced by adjusting cloud server parameters. In fact, this is a non-negligible issue during SFC deployment in 5G-MEC scenarios. Based on the above considerations, this paper constructs a joint SFC deployment problem for edge-cloud networks with the goal of maximizing network utility. We first propose a univariate modeling method based on meta-links that effectively avoids the variable coupling problem in traditional multivariate modeling approaches and reduce the problem size by at least half. Subsequently, to solve the NP-hard integer nonlinear problem (INLP), we propose a distributed computing architecture named SP-ADMM, which improves the speed and quality of SFC deployment in large-scale scenarios via convex combinatorial formulations and a Viterbi-based heuristic algorithm (PAC-GREP). Finally, we experimentally verify the convergence and approximation of the algorithms. Our solution demonstrates advantages in terms of network utility and convergence speed under the same network resources, increasing service capacity by at least 39%. © 2024 SPIE.

关键词： network function virtualization

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DPSFC: A Distributed Delay-Aware Approach for Improving Parallelized Service function Chains Placement 22

DPSFC: A Distributed Delay-Aware Approach for Improving Para...

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Zhang, Mingxin Ai, Yintan Li, Hua Inner Mongolia University College of Computer Science Hohhot China

ISBN: (纸本)9798331509712

network function virtualization (NFV) virtualizes traditional hardware-based network devices and intermediate boxes into Virtual network functions(VNF). A series of VNF through which packets pass constitute a Service function Chain(SFC). VNF can be placed as software on general-purpose commercial servers, greatly increasing the flexibility of network services and reducing costs. Packets need to pass through many VNFs to get from the source to the destination of an SFC. To reduce end-to-end delay caused by virtualization and chain length. SFC parallelization has been a successful solution. However, the existing Parallelized SFC(PSFC) placement method does not conform to the distributed design idea of network services. In this paper, we propose a distributed delay-aware PSFC placement approach called DPSFC that all VNF in PSFC are placed on different physical nodes as much as possible and balancing link propagation delay and VNF processing delay to reduce packet deposition at the merge node of parallel modules(pm). Finally, a link packet marking method is proposed to reduce the extra link bandwidth of distributed VNF placement. The simulation results show that compared with the existing approaches, our approach can improve the request acceptance ratio of PSFC while ensuring end-to-end delay. © 2024 IEEE.

关键词： network function virtualization

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Maximum Flow Routing Strategy for Space Information network With Service function Constraints

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第5期21卷 2909-2923页

作者： Yang, Huiting Liu, Wei Li, Hongyan Li, Jiandong Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Shaanxi Peoples R China

In this paper, we investigate the maximum flow routing strategy with the service function chain (SFC) constraints in the space information networks (SINs), where a SFC consists of a specific ordered sequence of service functions, and the mission flow must go through these functions in a predefined order. The time-varying SIN is modeled by the time-expanded graph (TEG). We formulate the maximum flow routing strategy problem with the SFC constraints as a linear programming (LP) problem. Furthermore, for a large-scale SIN, as the complexity of solving the LP problem is still very high, we propose a novel low-complexity SFC-constrained graph theory based (SFC-GT) algorithm. Specifically, we formulate this problem as one special single commodity maximum flow problem, where this flow must satisfy the SFC constraints. We first define the SFC-constrained residual network and the SFC-constrained augmenting path. Afterwards, we iteratively search the SFC-constrained augmenting path and update the SFC-constrained residual network. Simulation results demonstrate our proposed SFC-GT algorithm can achieve near-optimal performance with much less complexity.

关键词： Routing Complexity theory Satellites Wireless communication network topology Service function chaining Residual neural networks Space information network network function virtualization service function chain time-expanded graph single commodity maximum flow graph theory

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