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作者： Atoui, Wassim Sellil Assy, Nour Gaaloul, Walid Ben Yahia, Imen Grida SAMOVAR Telecom SudParis Paris France Computer Science Department Lebanese University Beirut Lebanon Orange Labs Paris France

Service providers in network function virtualization usually design manually or with static automation the deployment descriptors for virtual network functions. The descriptors are semi-structured files that contain information about the resource requirements and the operational behavior of virtual network functions. Designing the descriptors manually and without formal strategies is certainly a cumbersome and error-prone task for service providers. In this work, we propose a model-driven approach that assists service providers in designing the deployment descriptors. This approach uses a configurable model iteratively to give service providers insights on which best configuration to choose. Concretely, we propose (1) to use a configurable deployment descriptor model, (2) a learning approach based on machine learning to automatically construct the configurable model, and (3) an approach that learns configuration guidelines from a catalog of deployment descriptors to assist service providers with the selection of the configuration to use. The configurable deployment descriptor model captures the relation and also the variability between the virtualized network function (VNF) elements from different deployment descriptors. We propose a learning approach to build the configurable deployment descriptor model by finding and federating similar VNF elements from different deployment descriptors. With our machine learning approach, we construct automatically the configurable model from a set of deployment descriptors. We use afterward the configurable model to learn configuration guidelines from the deployment descriptors and recommend them for service providers. The results of our experiments highlight the effectiveness of our approach to learning configurable deployment descriptor models. © 2021 John Wiley & Sons, Ltd.

关键词： network function virtualization

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TIM: A trust insurance mechanism for network function virtualization based on trusted computing 1

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10th International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage, SpaCCS 2017

作者： Xu, Guangwu Tang, Yankun Yan, Zheng Zhang, Peng The State Key Lab of Integrated Services Networks School of Cyber Engineering Xidian University Xi’an710071 China Department of Communications and Networking Aalto University Espoo02150 Finland

ISBN: (数字)9783319723891

ISBN: (纸本)9783319723884

As a new network architecture and key technology of 5G, network function virtualization (NFV) is paid special attention in both industry and academia. In the context of NFV, Virtualized network functions (VNFs) located in different network computing platforms need collaborate to fulfill an expected networking service. Platform trust authentication and trusted collaboration should be highly ensured in order to support secure and trustworthy 5G mobile networks and wireless systems. However, such a mechanism is still missed in the literature. In this paper, we propose and develop a trust insurance mechanism, named TIM, based on Trusted Computing Platform (TCP) to realize trust authentication and achieve trusted collaboration among VNFs. Performance evaluation shows the effectiveness of TIM with regard to trust attestation accuracy, operation efficiency, and reasonable resource consumption. © 2017, Springer International Publishing AG.

关键词： network function virtualization

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Service chaining implementation in network function virtualization with software defined networking 17

Service chaining implementation in network function virtuali...

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5th International Conference on Communications and Broadband networking, ICCBN 2017

作者： Ziri, Salvatore Renato Samsudin, Ahmad Tajuddin Fontaine, Christophe Analytic and Computational Lab. Telekom Research and Development SDN. Bhd. Cyberjaya Malaysia CTO Office Qosmos Inc. Paris France

ISBN: (纸本)9781450348614

In this paper we are presenting Service function Chaining for network services in a virtualised environment. This kind of problem does not still have a commonly used solution. We have tested our design;explained in detail the issues of the currently used technologies;discussed the current custom solutions and the ITEF in-the-works;and shown our Proof of Concept. For this, we have recreated in our lab a virtual environment that includes different Virtual network functions and a Service Classifier, and we have monitored the traffic on the virtual network and on the Virtual network functions to make sure that all packets followed the correct path. The results of the test show that the solution is working and functional.

关键词： network function virtualization

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Enhancing network function virtualization and Service function Chaining: Innovative Optimization Strategies and Their Impact 1

Enhancing Network Function Virtualization and Service Functi...

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1st International Conference on Pioneering Developments in Computer Science and Digital Technologies, IC2SDT 2024

作者： Upadhyay, Deepak Gupta, Mridul Sharma, Kunj Bihari Upadhyay, Abhay Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350365016

Throughout this paper, the reader was able to better understand how innovative optimization techniques through NFV and SFC frameworks could and should be applied to address the developing and shifting focus of contemporary network infrastructures. Focusing on performance metrics performance via latency, throughput, resource utilization, and operational cost, the presented algorithms and machine learning models developed and executed due to this research showed innovative and dynamic optimization of network functions. Through further extensive simulations equalling 125 seconds, our findings reported creative results of improving performance in several significant areas: latency was reduced, throughput was enhanced, resource utilization was more efficient, and operational cost was reduced. These results indicated that our optimization strategies can pay off and bring a number of benefits to NFV and SFC that address a clear need for change in the current type of network management models. Therefore, this paper is valuable and serves as a testament of our strategies' power along with opening various doors for following network optimization research. Therefore, one can see how important it is to implement innovation in the face of change. © 2024 IEEE.

关键词： network function virtualization

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Communication network node fault recovery strategy under network function virtualization

Communication network node fault recovery strategy under net...

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2020 International Conference on Virtual Reality and Intelligent Systems, ICVRIS 2020

作者： Xiao-Lan, Yu Chongqing City Vocational College Yongchuan Chongqing402160 China

ISBN: (纸本)9781728196367

In order to improve the output stability of communication network nodes, a fault recovery strategy of communication network nodes based on channel equalization scheduling under the virtualization of network functions is proposed. The channel model of wireless communication network under the condition of virtual network function is established, and the communication channel equalization is designed by Porter interval equalization scheduling method, function virtualization, the phase shift of output channel of each node is obtained, and the impulse response of analog channel under the condition of network function virtualization is obtained. The simulation results show that this method has good adaptability to the fault recovery of communication network nodes, reduces the output error rate of communication network, and improves the transmission fidelity of communication network nodes. © 2020 IEEE.

关键词： network function virtualization

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Stochastic network Calculus for network function virtualization in Underwater Wireless Sensor networks 1

Stochastic Network Calculus for Network Function Virtualizat...

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1st International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2022

作者： Ponraj, T.C. Subash Sukumaran, Rajeev Vignesh, S.R. Saravanan, M. Manikandan, T.T. Radhakrishnan, M. Srm Institute of Science and Technology Computer Science and Engineering Chennai India Srm Institute of Science and Technology Department of Mathematics Chennai India

ISBN: (纸本)9781665436472

Underwater Wireless Sensor networks is a popular sub domain of WSN. The Number of Ocean monitoring applications is increasing day-by-day. For effective operations of such underwater applications service provisioning plays a major role. network function virtualization (NFV) has been considered as an effective technology to make flexible service provisioning in terrestrial network. Since UWSN also demands such flexible service provisioning capability, NFV can be adapted for UWSN as well. By providing network operations through NFV in UWSN operational consumptions and capital expenses will be reduced drastically. So, this research focuses on modeling end-end performance bounds on NFV based UWSN using Stochastic network Calculus (SN C). Monitoring applications in UWSN expects on demand service provisioning capability from the underlying network. In order to model such on demand service provisioning features and capability of NFV, we have taken into account both the non-bursty and bursty type of traffic of UWSN. In UWSN for modeling estimation of current resource availability of Virtual network function nodes with multi-level traffic and their complicated NFV chain, using leftover service property and convolution associativity property of SNC has been used. The proposed mathematical model of NFV service provisioning in UWSN has been evaluated for its correctness using a simulation model. The results of the simulation model and the proposed analytical model have a very negligible difference. So, the proposed model can be adapted in real time of effective NFV based service provisioning in UWSN. © 2022 IEEE.

关键词： network function virtualization

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Dynamic Spectrum Management with network function virtualization for UAV Communication

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2021年第2期101卷 40-40页

作者： Xu, Zhengjia Petrunin, Ivan Tsourdos, Antonios Cranfield Univ Sch Aerosp Transport & Mfg Wharley End MK43 0AL England

Rapid increases in unmanned aerial vehicles (UAVs) applications are attributed to severe spectrum collision issues, especially when UAVs operate in spectrum scarce environments, such as urban areas. Dynamic air-to-ground (A2G) link solutions can mitigate this issue by utilizing programmable communication hardware in the air and real-time assignment of spectrum resources to achieve high-throughput and low-latency connectivity between UAVs and operators. To mitigate the high-computation issue among ground control station (GCS) networks and provide a broad communication coverage for large number of UAVs, we propose an advanced UAV A2G communication solution integrated with the dynamic spectrum management (DSM) and network function virtualization (NFV) technology to serve urban operations. The edge-cutting UAV communication technologies are surveyed. The proposed scheme is discussed in terms of the high-level system architecture, virtual network architecture, specific virtual functions (SVFs), and affiliated operation support databases. Some major research challenges are highlighted and the possible directions of future research are identified.

关键词： Aeronautical cognitive communication Air-to-ground communication Virtual network UAV communication network function virtualization Urban communication

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Virtual network Resource Optimization Model for network function virtualization

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WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2021年第1期2021卷

作者： Vladislavi, Dani Huljenic, Darko Ozegovic, Julije Ericsson Nikola Tesla Dd Zagreb Croatia Univ Split Fac Elect Engn Mech Engn & Naval Architecture Split Croatia

network function virtualization (NFV) is a concept aimed at achieving telecom grade cloud ecosystem for new-generation networks focusing on capital and operational expenditure (CAPEX and OPEX) savings. This study introduces empirical throughput prediction model for the virtual network function (VNF) and network function virtualization infrastructure (NFVI) architectures based on Linux kernel. The model arises from the methodology for performance evaluation and modeling based on execution area (EA) distribution by CPU core pinning. EA is defined as a software execution unit that can run isolated on a compute resource (CPU core). EAs are derived from the elements and packet processing principles in NFVIs and VNFs based on Linux kernel. Performing measurements and observing linearity of the measured results open the possibility to apply model calibration technique to achieve general VNF and NFVI architecture model with performance prediction and environment setup optimization. The modeling parameters are derived from the cumulative packet processing cost obtained by measurements for collocated EAs on the CPU core hosting the bottleneck EA. The VNF and NFVI architecture model with performance prediction is successfully validated against the measurement results obtained in emulated environment and used to predict optimal system configurations and maximal throughput results for different CPUs.

关键词： network function virtualization

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A Component-based Middleware for network function virtualization

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JOURNAL OF INTERNET TECHNOLOGY 2018年第6期19卷 1645-1655页

作者： Chen, Yung-Chiao Ma, Yi-Wei Chiang, Cheng-Mou Chen, Jiann-Liang Natl Taiwan Univ Comp & Informat Networking Ctr Taipei Taiwan Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan

A Software Definition network (SDN) supports programmable, flexible and convenient network management. network functions virtualization (NFV) virtualizes multiple types of network services, reducing the complexity of network construction. The above two technologies work together to improve the efficiency of network construction and facilitate network maintenance. This study concerns the design of component-based middleware with high performance and reliability for NFV. The middleware responds to user needs in configuring network functions. When the load changes, it adjusts the virtual machine configuration to ensure that users can receive quality service. The proposed middleware platform includes the network, NFV and a Resource Manager to improve the operational effectiveness and reliability of the network. network performance is analyzed identify the proposed method that minimizes the cost of construction a network resource service chain. The proposed middleware can eliminated the service bottleneck of NFV, and the results of the performance analysis demonstrate that it improves network performance by 30% and reliability by 1.5%.

关键词： Software-defined networking network function virtualization Middleware Service chain Resource allocation

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Distributed LSTM-based cloud resource allocation in network function virtualization Architectures

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COMPUTER networkS 2022年 213卷 1页

作者： Catena, Tiziana Eramo, Vincenzo Panella, Massimo Rosato, Antonello Univ Roma La Sapienza Dept Informat Engn Elect & Telecommunicat Via Eudossiana 18 I-00184 Rome Italy

The high reconfiguration time of cloud resources in network function virtualization environments has led to the proposal of prediction-based resource allocation algorithms, with extensive use of artificial intelligence techniques. The prediction of processing capacities performed jointly and centrally has proved to be very complex due to the high communication overhead required. For this reason, we propose a distributed prediction technique in which Long Short-Term Memory neural networks exchange only a few weights in order to drastically reduce the communication overhead compared to the centralized case. We propose and investigate three different distributed solutions and show how they allow for low prediction errors.

关键词： network function virtualization Long Short-Term Memory Neural network Resource allocation

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