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IEEE Conference on network function virtualization and Software Defined networks (NFV-SDN)

作者： Jhonattan Cabral Augusto Venâncio Neto Helber Wagner da Silva Federal University of Rio Grande do Norte (UFRN) Natal RN Brazil Instituto de Telecomunicações Portugal Federal Institute of Rio Grande do Norte (IFRN) Canguaretama RN Brazil

ISBN: (数字)9798350380538

ISBN: (纸本)9798350380545

In the rapidly evolving 5G connectivity era, cyber-security is critical for protecting mission-critical applications and sensitive data. The need for delivering mobile "killer apps" introduces significant cyber threats and vulnerabilities. The programmable capabilities and centralized Software-Defined networking (SDN) management enhance protection in 5G mobile networks, but yields potential risks by the centralized infrastructure control, thus jeopardizing security and reliability. Recent research put forward using Machine Learning (ML) technique to address these intrusion detection and mitigation mechanisms preemptively. This paper proposes the predictive SDN Intrusion Detection (pSID) system, which lies in ML to predict and neutralize cyber threats in a proative approach. Evaluated in a realistic testbed, pSID effectively identifies and mitigates threats before causing significant harm, highlighting the importance of proactive cybersecurity measures within SDN frameworks.

关键词： 5G mobile communication Prevention and mitigation Mission critical systems Intrusion detection Machine learning network function virtualization Reliability Software defined networking Protection Computer security

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Measurement-as-a-Service: VNF-to-VNF Performance Measurement in Federated Testbed

Measurement-as-a-Service: VNF-to-VNF Performance Measurement...

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Engineering Informatics, IEEE

作者： Ashit Kumar Subudhi Federico Civerchia Francesco Giannone Piero Castoldi Luca Valcarenghi Koteswararao Kondepu Indian Institute of Technology Dharwad Dharwad India Scuola Superiore Sant’Anna SmaRTy Italia srl Cassina de’ Pecchi Pisa Italy Scuola Superiore Sant’Anna Pisa Italy

ISBN: (数字)9798331505776

ISBN: (纸本)9798331505783

In 5G and beyond, network function virtualization (NFV) and Software Defined networking (SDN) technologies enables an easy deployment of Virtualized network functions (VNF). However, designing and building scalable NFV infrastructure is quite challenging to adopt and making VNFs deployment on existing hardware. To understand such behaviour, the EU SoftFire project developed federated virtualization testbed for NFV/SDN experiments. This paper outlines the SoftFire Middleware framework and proposes an automated Measurement-as-a-Service (MaaS) for performing VNF-to-VNF performance metrics, such measurements can be exploited by an orchestrator to perform VNF instantiate selection.

关键词： Measurement 5G mobile communication Bandwidth Throughput Hardware network function virtualization Software defined networking virtualization Middleware Informatics

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An online service function chain orchestration method for profit maximization in edge computing networks

ENGINEERING REPORTS

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ENGINEERING REPORTS 2023年第9期5卷

作者： Yang, Chen Hu, Bingtao Feng, Yixiong Huang, Hua Lai, Haoshan Tan, Jianrong Zhejiang Univ State Key Lab Fluid Power & Mechatron Syst Hangzhou Peoples R China China Unicom Zhejiang Ind Internet Co Ltd Hangzhou Peoples R China Zhejiang Univ Technol Dept Comp Sci Hangzhou Peoples R China Zhejiang Univ Dept Mech Engn Hangzhou 310058 Peoples R China

network function virtualization (NFV) is an appealing solution that transforms complex network functions from dedicated hardware to software instances running in a virtualized environment. However, some new challenges will arise when deploying virtual network functions to meet the needs of NFV and edge-computing (EC) enabled 5G networks. In this paper, we focus on the service function chain (SFC) orchestration problem for EC-enabled networks to maximize the profit of network service providers. First, the mathematical model of SFC orchestration in NFV and EC-enabled networks is defined. Then, a two-stage heuristic algorithm is proposed to optimize the total revenue. Finally, the performance of the method is evaluated by simulation experiments and the results show its effectiveness.

关键词： edge computing network function virtualization service function chain orchestration

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Optical Cross-Connect Technologies for Flexible Optical networks

Optical Cross-Connect Technologies for Flexible Optical Netw...

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Automation and Computation (AUTOCOM), International Conference on

作者： Prateek Aggarwal Sireesha Nanduri Poonguzhali S B.P. Singh Satya Ranjan Das Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India School of Mangement - PG Management JAIN (Deemed to be University) Bangalore Karnataka Department of Electronics and Communication Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Various optical cross-connect technologies are being developed for flexible next-generation optical networks to ensure the efficiency of real-time optical network routing. Demand for larger bandwidth and faster data transmission continues to grow. Therefore, these networks are becoming more and more significant. Conventional optical cross-connects offer limited scalability, and they need to be more flexible by nature due to their traditional architecture, hindering fast adaptation to altering traffic patterns. A solution to this problem is the new OXC technologies, which allow dynamic and reconfigurable optical networks. These technologies use high-end optics and electronics, including wavelength-selective switches and coherent receivers, to offer routing and switching flexibility. One key benefit of flexible OXC technologies is that their capabilities to support different transmission formats and data rates cater well to specific service requisites. They also allow for greater implementation of software-defined networking principles, creating centralized control and management over the network. Moreover, flexible OXCs enable efficient tower best practices and O&M savings through reduced manual network intervention.

关键词： Optical fibers Optical switches Scalability Bandwidth Optical fiber networks Wavelength division multiplexing Optical receivers Real-time systems network function virtualization Software defined networking

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Trustworthy Execution of O-RAN Applications by strong Separation and minimal Trusted Computing Base

Trustworthy Execution of O-RAN Applications by strong Separa...

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IEEE Conference on network function virtualization and Software Defined networks (NFV-SDN)

作者： Jana Eisoldt Till Miemietz Barkhausen Institut Dresden Germany

O-RAN allows the integration of virtualised third-party applications (xApps) for near-real time control of the Radio Access network. We aim to minimise the risks of privilege escalation and kernel compromise by utilis... 详细信息

ISBN: (数字)9798350380538

ISBN: (纸本)9798350380545

关键词： Trusted computing Open RAN Containers network function virtualization Software defined networking Kernel

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Applying Evolutionary Algorithms for Service function Chaining in 5G networks

Applying Evolutionary Algorithms for Service Function Chaini...

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Congress on Evolutionary Computation

作者： A.M. Mora J. Victoria-Mohammed N. Medina-Medina J.F. Valenzuela-Valdés Dept. Signal Theory Telematics and Communications University of Granada Granada Spain Dept. Languages and Computer Systems University of Granada Granada Spain

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

The recent boom of 5G networks, coupled with the escalating demand among users for higher-capacity connections, is presenting a formidable challenge. 5G networks encompass a diverse array of advantageous technologies, prominently including Software- Defined networking (SDN) together with network function virtualization (NFV), in which a key problem is the optimal development of Service function Chaining (SFC). This paper presents two approaches based on Genetic Algorithms (GAs), for the optimal composition of SFCs focused on network pathways, and tailored for the service chain required in different 5G connections (user service requests). The approaches have been tested on different instances of the problem with topologies including 6, 19 and 52 nodes. The obtained results are promising, showing optimal paths inside simple and complex topologies for every connection as well as for multiple connections.

关键词： 5G mobile communication Service function chaining network topology Evolutionary computation Topology network function virtualization Optimization

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Power Consumption-Aware 5G Edge UPF Selection using Deep Reinforcement Learning

Power Consumption-Aware 5G Edge UPF Selection using Deep Rei...

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IEEE Conference on network function virtualization and Software Defined networks (NFV-SDN)

作者： Arturo Bellin Nicola Di Cicco Daniele Munaretto Fabrizio Granelli Department of Information Engineering and Computer Science (DISI) University of Trento Italy Research and Innovation Department Athonet a HPE Acquisition Bolzano Vicentino Italy Department of Electronics Information and Bioengineering (DEIB) Politecnico di Milano Italy

ISBN: (数字)9798350380538

ISBN: (纸本)9798350380545

In this paper, we propose a Deep Reinforcement Learning (DRL) algorithm for the orchestration of an edge-cloud 5G core network deployment with multiple distributed User Plane function (UPF) instances. More specifically, our DRL agent provides a policy for the UPF selection procedure when a new connection from a user to the data network is established. The choice of UPF is based on the real-time power consumption metrics gathered from the edge and cloud hosts in addition to the latency and bandwidth requirements of the users. The overall objective is to minimize the system power consumption while satisfying the desired quality of service. We show that the proposed algorithm performs better than other heuristics, resulting in lower power consumption and fewer errors in the latency requirements. Finally, we show the advantages of leveraging the power consumption data instead of CPU utilization metrics as often used in the literature.

关键词： Measurement Cloud computing Power demand 5G mobile communication Heuristic algorithms Quality of service Deep reinforcement learning Real-time systems network function virtualization Software defined networking

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Framework for Securing Quality Control Process in Engineering Using IOT based Machine Learning Models

Framework for Securing Quality Control Process in Engineerin...

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Intelligent & Innovative Practices in Engineering & Management (IIPEM), International Conference on

作者： Manoj Kumar Nigam Pravin B Khatkale Tarun Dhar Diwan Sandeep Roy Abhishek Badholia Onkar Ghige Department of Electrical Engineering Kalinga University Naya Raipur India Sanjivani University Kopargaon Maharashtra India Atal Bihari Vajpayee University Bilaspur India Department of Data Science Shri Shankaracharya Institute of Professional Management and Technology Raipur Department of Elecrical Engineering Sanjivani College of Engineering Kopargaon MH India

ISBN: (数字)9798350390049

ISBN: (纸本)9798350390056

The study aims to investigate how combining many technologies may improve the scalability, adaptability, and security of network engineering systems. Some of the technologies that come under this category include the Internet of Things (IoT), network function virtualization (NFV), Machine Learning (ML), and Software Defined networking (SDN). Examining potential effective merger strategies for these technologies is one of the study's objectives. Our study has shown that our approach improves organizational effectiveness, defect finding, and engineering productivity. This is accomplished via the use of machine learning (ML) and the Internet of Things (IoT) to real-time data collecting, predictive analytics, and quality control assurance. By making use of these two technologies, this assignment may be successfully completed. The case studies demonstrate the potential of our suggested machine learning models to decrease training time and improve engineering quality control assessment accuracy. The fact that our models can do both of these tasks in comparison to earlier machine learning models serves as evidence for this.

关键词： Training Accuracy Scalability Machine learning Quality control Real-time systems network function virtualization Internet of Things Security Software defined networking

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Multi-Objective Virtual network functions Placement and Traffic Routing Problem

Multi-Objective Virtual Network Functions Placement and Traf...

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Congress on Evolutionary Computation

作者： Nguyen Thi Tam Tran Ho Khanh Ly Bui Trong Duc Tran Huy Hung Huynh Thi Thanh Binh Hanoi University of Science and Technology Hanoi Vietnam VNU University of Science Vietnam National University Hanoi

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Presently, the Internet infrastructure continues to be improved to satisfy the growing demands of users. Installing hardware devices in the network's server center faces many limitations, such as difficulties in device replacement, high investment costs, and operating expenses. The emergence of network function virtualization (NFV) technology has addressed these drawbacks. This technology replaces dedicated hardware with software running in a virtualized environment, offering a more flexible and scalable solution. However, resource allocation is a critical concern in NFV networks. Proper resource allocation can enhance service quality and reduce network deployment costs. This paper investigates the network resource allocation problem to achieve two objectives: i) reduce network deployment costs and ii) decrease the latency of service chains in the network. We propose the modification of Non-dominated Sorting Genetic Algorithm 2, called NSGA2-H, to solve the multi-objective problem. The distinctive feature of the proposed algorithm, compared to the traditional NSGA2, is the use of a selective mutation operator. This mutation occurs on individuals at the first front, resembling a shift operation to enhance the algorithm's exploration capability. Experimental results on real-world datasets have demonstrated the effectiveness of the proposed algorithm.

关键词： Measurement Costs Adaptive systems Heuristic algorithms Dynamic scheduling Hardware network function virtualization

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External Memories of PDP Switches for In-network Implementable functions Placement: Deep Learning Based Reconfiguration of SFCs

External Memories of PDP Switches for In-Network Implementab...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Somayeh Kianpisheh Tarik Taleb Centre for Wireless Communications University of Oulu Finland Ruhr University Bochum Germany

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

network function virtualization leverages programmable data plane switches to deploy in-network implementable functions, to improve QoS. The memories of switches can be extended through remote direct memory access to access external memories. This paper exploits the switches external memories to place VNFs at time intervals with ultra-low latency and high bandwidth demands. The reconfiguration decision is modeled as an optimization to minimize the deployment and reconfiguration cost, while meeting the SFCs deadlines. A DRL based method is proposed to reconfigure service chains adoptable with dynamic network and traffic characteristics. To deal with slow convergence due to the complexity of deployment scenarios, static and dynamic filters are used in policy networks construction to diminish unfeasible placement exploration. Results illustrate improvement in convergence, acceptance ratio and cost.

关键词： Deep learning Costs Filters Service function chaining Quality of service network function virtualization Complexity theory Global communication Optimization Convergence

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