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

作者： Rodrigo De B. Lira Lucas V. Monteiro Vinícius S. Simão Leandro C. De Almeida Ruan D. Gomes Otacílio De A. Ramos Neto Paulo Ditarso Maciel IFPB Innovation Hub - Smart4i Laboratory João Pessoa PB Brazil Academic Unit of Informatics Instituto Federal da Paraíba (IFPB) João Pessoa PB Brazil

ISBN: (数字)9798350380538

ISBN: (纸本)9798350380545

5G technology holds great promise for Industry 4.0 with its high-speed, low-latency, and reliable connectivity. However, deploying private 5G networks is challenging due to high costs and technical complexities. This work offers a solution by creating a virtualized private 5G infrastructure using Infrastructure as Code (IaC) and fostering network programmability experimentation. Using tools like KVM, free5GC, and UERAN-SIM, the setup simulates 5G scenarios, particularly for real-time video transmission, enabling cost-effective experimentation and research without the need for extensive physical infrastructure. The demonstration emphasizes automation and virtualization to simplify 5G network deployment for industrial applications.

关键词： Costs 5G mobile communication Streaming media Real-time systems network function virtualization Fourth Industrial Revolution Reliability virtualization Software defined networking Low latency communication

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Low latency and resilient industrial network with next generation SDN and PLC virtualization

Low latency and resilient industrial network with next gener...

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MILCOM, Military Communications Conference

作者： Taposh Kumer Sarker Deepak K. Tosh Department of Computer Science University of Texas at El Paso El Paso USA

ISBN: (数字)9798350374230

ISBN: (纸本)9798350374247

The critical infrastructure and industrial control systems (ICS) typically function in isolation and make use of specialized hardware, software, protocols that are often sourced from heterogeneous vendors. Rise of Industry 4.0 and Industrial Internet of Things (IIoT) means that these isolated old networks are gradually being connected with Internet and other telecommunication networks. This leads to various problems and challenges, such as incompatibility with outside networks, cyber security challenges, limited automation, lack of features or mechanisms demanded by modern devices and sensors. On the other hand an ICS has strict operational requirements from the network, such as reliability, temporal consistency, ruggedness etc. Emerging technology like network function virtualization (NFV), and software defined network (SDN) have excellent opportunity to achieve network resiliency in ICS, however their application has been under-explored. Therefore, we present a novel architecture for industrial control networks (ICN) that take advantage of NFV and SDN to build robust, cost effective, secure, and scalable ICNs. We leverage the novel P4 paradigm to virtualize the network infrastructure and evaluate its effectiveness.

关键词： Industrial control Sensor phenomena and characterization Software network function virtualization Software reliability Telecommunication network reliability Software defined networking virtualization Industrial Internet of Things Resilience

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Robustness Aware SFC Placement in NFV-Enabled Multi-Domain networks Under Resource Demand Uncertainty

Robustness Aware SFC Placement in NFV-Enabled Multi-Domain N...

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International Conference on Dependable Systems and Their Applications (DSA)

作者： Chuangchuang Zhang Shou-Yu Lee Pan Liu Hongyong Yang William Cheng-Chung Chu School of Information and Electrical Engineering Ludong University Yantai China Department of Computer Science Tunghai University Taiwan Faculty of Business Information Shanghai Business School Shanghai China School of Computing and Artificial Intelligence Fuyao University of Science and Technology China

ISBN: (数字)9798331532390

ISBN: (纸本)9798331532406

The increasing service demands in 5G networks have led to the emergence of network function virtualization (NFV) technology. Through the virtualization technique, NFV enables on-demand and flexible service provisioning and deployment by implementing networks functions in forms of software instances, called Virtual network functions (VNFs). With the rapid development and implementation of 5G, the Service function Chain (SFC) placement problem in multi-domain network scenarios is gaining significant attentions due to the sudden and dynamic patterns of resource demands from a diversity of service requests. Most existing proposals attempt to optimize the SFC placement in multi-domain networks, under the assumption that resource demand required each service request is given in prior and keeps unchanged during the SFC execution period. However, it is impractical in real network scenarios due to the evolving dynamic changes of service requests. The uncertainty of service demands has an important effect on service reliability, service quality and network performance. To this end, in this paper, we study the problem of robust SFC placement in multi-domain networks under the assumption that resource demands of SFC requests are uncertain. We first formulated the problem of robust SFC placement in multi-domain networks as an integer programming model with the aim to minimize the SFC placement cost while considering the Quality of Service (QoS) guarantee. Then, we develop a three-stage heuristic placement algorithm to solve the problem. The extensive simulation results demonstrate that our proposed heuristic algorithm is efficient and can save more placement cost than comparison mechanisms.

关键词： Integer programming Costs Uncertainty 5G mobile communication Heuristic algorithms Simulation Quality of service Software network function virtualization virtualization

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VMFMAX: Improving Virtual Machine Utilization in VNF Placement

VMFMAX: Improving Virtual Machine Utilization in VNF Placeme...

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IEEE Symposium on Systems and Information Engineering Design, SIEDS

作者： Seyedreza Taghizadeh Parnian Emami Hamid Reza Taleghani Ali Tarmah Seyedehnarjes Taghizadeh Department of Computer Science Engineering and Information Technology Shiraz University Shiraz Iran Department of Electrical and Computer Engineering Shiraz University Shiraz Iran Department of Information Technology NASINE Co. Shiraz Iran

ISBN: (数字)9798350385144

ISBN: (纸本)9798350385151

In order to improve the performance of contemporary and prospective technologies grounded in network function virtualization (NFV), it is imperative to concentrate on identifying the most effective strategies for the placement of Virtual network functions (VNFs) within NFV frameworks. Consequently, the objective of this study is to present a viable solution for VNF placement. We delve into the significance of factors such as Storage Latency, CPU Model, and network Packet Dropped, among others, which necessitate careful consideration. These parameters wield substantial influence over Virtual Machines (VMs) and overall VNF placements. Through the judicious selection of suitable VMs for VNFs, our aim is to improve the placements of VNFs, employing our proposed methodology termed VMFMAX. Our findings reveal that VMFMAX has efficient and less time and resource-consuming calculations compared to previous studies. VMFMAX conspicuously impacts the outcomes of the VNF placement process, underscoring its critical role in achieving more precise and accurate calculations.

关键词： Merging Random access memory Virtual machining network function virtualization Spreadsheet programs

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Bring functions Back to the network: A Measurement Study

Bring Functions Back to the Network: A Measurement Study

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

作者： Stefan Senk Marian Ulbricht Hosein K. Nazari Tung V. Doan Giang T. Nguyen Frank H. P. Fitzek Deutsche Telekom Chair of Communication Networks TU Dresden Germany Haptic Communication Systems TU Dresden Germany Centre for Tactile Internet With Human-in-the-Loop (CeTI) TU Dresden Germany

ISBN: (数字)9798350380538

ISBN: (纸本)9798350380545

network function virtualization (NFV) is envisioned to provide the foundation for a dynamic, high-performance multi-layer network architecture. With NFV, running network functions on general-purpose hardware is supposed to lower network latency due to reduced propagation delay. The trade-off, however, is in impaired reliability and increased processing latency, which could negatively affect Quality of Service (QoS) and Quality of Experience (QoE). We investigate the tradeoff via a comprehensive measurement study exploiting a high-precision measurement method on a carrier-grade Cisco Catalyst 9500 Series switch, which provides enhanced computing capability via lightweight containerization. Baseline results on packet forwarding latency confirm that software-based forwarding is inferior to the hardware pendant. Subsequently, we deploy a more realistic application with an example for network coding and introduce a new metric, re-coding opportunities. Our study identifies a superior performance of generic hardware, but also shows advantages of in-network computing for latency-tolerable scenarios.

关键词： Performance evaluation Quality of service Switches Hardware network function virtualization Quality of experience Reliability Software defined networking Stress Propagation delay

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The dynamic job assignment problem in grid computing: A comparative study of two optimization methods

The dynamic job assignment problem in grid computing: A comp...

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World Congress on Computing and Communication Technologies (WCCCT)

作者： Régis Donald Hontinfinde Ariel Kamoyedji Mahugnon Géraud Azehoun Pazou Marcos Thyrbus Vitouley Roland Sèmako Honfo Christian Djidjoho Akowanou Laboratory of Science Engineering and Mathematics University of Abomey (UNSTIM) Abomey Republic of Benin Department of Information and Communication Systems Okayama University Okayama Japan

ISBN: (数字)9798350372328

ISBN: (纸本)9798350372335

The advent of the Software Defined networking (SDN) and network function virtualization (NFV) technologies in the field of telecommunications has led to a tremendous reduction of costs as well as an increase in terms of infrastructure flexibility. Thus, equipments that play a pivotal role in telecommunications have merely been replaced by computers and their functions have accordingly been softwarized. To further reduce costs, some telecommunications carriers are now considering using decentralized grid computing-based networks to route a part of their traffic. The user-PC computer system (UPC) system is a technology for pooling and making available the unused computing resources (CPU) of the personal computers (PC) of members belonging to the same organization. For instance, in the drug discovery, economic forecasting, seismic analysis fields that deal with computationally intensive problem solving, Grid Computing has become an essential tool for building an affordable computing environment. We have previously designed an efficient static job scheduling genetic algorithm considering CPU core utilization for the UPC system. It finds an optimal assignment that minimizes the processing time of the available set of jobs in a static scenario, i.e., jobs are all available in the beginning and all worker PCs are idle. However, in reality, jobs join and leave the system dynamically and therefore, when new jobs join the system, some workers may be busy. In this paper, we propose an extension of our previously proposed static job scheduling genetic algorithm, that considers dynamic job scheduling in the UPC system. We conducted experiments using six worker PCs and up to 51 jobs. A comparative study of the results obtained using our dynamic scheduling genetic algorithm showed an improvement of about 13.67% in Makespan compared to that of the Dynamic Randomized Multi-Start Local Search (DRMSLS)-based method.

关键词： Costs Processor scheduling Heuristic algorithms Dynamic scheduling Grid computing Telecommunications network function virtualization

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Optimizing VNF Migration in B5G Core networks: A Machine Learning Approach

Optimizing VNF Migration in B5G Core Networks: A Machine Lea...

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International Conference on Smart Communications and networking (SmartNets)

作者： Brahma Reddy Tanuboddi Gad Gad Zubair Md Fadlullah Mostafa M. Fouda Department of Computer Science Western University London ON Canada Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA Center for Advanced Energy-Studies- (CAES) Idaho Falls ID USA

ISBN: (数字)9798350385328

ISBN: (纸本)9798350385335

Software-Defined networking (SDN) is an innovative networking paradigm that fundamentally changes the way network management and operation are approached. network functions virtualization (NFV) is a network architecture concept that leverages standard IT virtualization technology to virtualize entire classes of network node functions into building blocks that can be connected or chained together to create communication services. NFV is part of the broader trend towards the virtualization of IT services and infrastructure. When combined with SDN, it provides a complete solution for a fully virtualized network, offering unprecedented levels of agility and efficiency. The concept of Virtual network function (VNF) migration has introduced the need for optimized algorithms to minimize migration time and costs, addressing a critical aspect of resource utilization. This paper explores the utilization of machine learning methods, especially neural networks to enhance the migration of VNFs, and presents a framework leveraging Convolution Neural networks (CNN) and Artificial Neural networks (ANN) to predict optimal migration paths for VNFs, aiming to minimize migration time and cost. The proposed solution analyzes network conditions, workload patterns, and resource availability, enabling dynamic and efficient VNF re-Iocations. This approach significantly improves network performance and reliability, making it a vital contribution to the field of network function virtualization.

关键词： Technological innovation Costs Machine learning algorithms Convolution Artificial neural networks Machine learning network function virtualization

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A Review of Secure IoT Based Smart Health Monitoring System using Blockchain Technique

A Review of Secure IoT Based Smart Health Monitoring System ...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： Rucha Patel Vedvyas Dwivedi Department of Electronics & Communications Indus University Ahmedabad India

ISBN: (数字)9798350396157

ISBN: (纸本)9798350396164

The integration of the Internet of Things (IoT) with blockchain technology is significantly transforming smart health monitoring systems. IoT enables the seamless collection of health data, while blockchain's decentralized ledger ensures the integrity and security of this data, mitigating potential breaches. This symbiosis addresses current healthcare challenges by enhancing security, transparency, and efficiency, fostering a patient-focused and reliable monitoring system. With the rise of the Medical Internet of Things (MIoT), personalized and cost-effective healthcare solutions are more accessible, thanks to technologies like Wireless Body Area networks (WBAN), which improve data quality, and Machine Learning (ML), which effectively processes large datasets. Fog Computing has been instrumental in ensuring efficient data communication with reduced latency, and advancements in Software-Defined networking (SDN) and network function virtualization (NFV) offer simpler, adaptable networks for healthcare. However, increased data volume raises privacy and security concerns, propelling a shift towards blockchain for enhanced data protection and transparency. Innovations like blockchain-based federated learning aim to safeguard privacy without compromising model accuracy, and smart contracts on platforms like Hyperledger Fabric provide secure patient history logs and immediate access to medical records. Tools such as the Libelium e-Health toolkit further aim to revolutionize monitoring, diagnosis, and treatment processes.

关键词： Wireless communication Smart healthcare Body area networks Blockchains network function virtualization Security Internet of Things

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MEC in the 5G Era: Enhancing Reliability Through Backup Strategies and Technology Integration

MEC in the 5G Era: Enhancing Reliability Through Backup Stra...

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International Conference on Transparent Optical networks

作者： Maryam Masoumi Fabrizio Brasca Emanuele Bonfani Gianluca Rizzi Ignacio De Miguel Ramón J. Durán Barroso Universidad de Valladolid Spain WindTre SpA Italy

ISBN: (数字)9798350377323

ISBN: (纸本)9798350377330

Understanding the unique features of Multi-access Edge Computing (MEC) in the context of 5G is key, as they enable applications such as real-time analytics. This paper explores the integration of 5 G technologies with MEC and the challenges in deploying and maintaining MEC infrastructure, recognizing the impact on network reliability. In particular, the paper considers potential failures in MEC and their broader consequences on overall network reliability, proposing the strategic use of backup resources as a proactive solution to fortify MEC resilience. MEC, evolving as an ecosystem to integrate telecommunication and IT services, establishes a cloud computing platform at the edge of the radio access network (RAN), enhancing storage and computational capabilities with reduced latency for mobile end-users. The analysis covers key technologies enabling MEC integration with 5G, including software-defined networking (SDN), network function virtualization (NFV), and network slicing. The deployment of network Services (NS) through virtual network functions (VNFs) is explored for latency-sensitive communication services, acknowledging the vulnerability of softwarized and cloud services to failures. Reliability emerges as a major challenge in MEC 5G networks, prompting the proposal of redundancy (backup) as a solution to enhance communication service reliability, setting the stage for further research considerations in MEC reliability.

关键词： Cloud computing 5G mobile communication Ecosystems Real-time systems network function virtualization Reliability Telecommunication network reliability

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Review and Analysis of Recent Advances in Intelligent network Softwarization for the Internet of Things

arXiv

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arXiv 2024年

作者： Zormati, Mohamed Ali Lakhlef, Hicham Ouni, Sofiane Compiègne France University of Carthage Tunis Tunisia

The Internet of Things (IoT) is an emerging technology that aims to connect heterogeneous and constrained objects to each other and to the Internet. It has grown significantly in a wide variety of applications such as smart homes, smart cities, smart vehicles, etc. The huge number of connected devices increases the challenges, as IoT provides diverse and complex network services with different requirements on a common infrastructure. network Softwarization is the latest network paradigm that transforms traditional network processes to the separation of hardware and software by using some enabling network technologies such as Software Defined networking (SDN) and network function virtualization (NFV). Machine Learning (ML) plays an essential role in creating smarter IoT networks, as it has shown remarkable results in various domains. Given that the network softwarization allows it to be easily integrated, ML can play a crucial role in efficient and self-adaptive IoT networks. In this paper, we provide a detailed overview of the concepts of IoT, network softwarization, and ML, and we study and discuss the state of the art of intelligent ML-enabled network softwarization for IoT. We also identify the most prominent future research directions to be considered. © 2024, CC BY-NC-ND.

关键词： network function virtualization

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