Network Functions Virtualization (NFV)

2021 ◽  
pp. 155-184
Author(s):  
Diego R. Lopez ◽  
Pedro A. Aranda
Keyword(s):  
State Of The Art ◽  
Network Services ◽  
Service Provisioning ◽  
It Services ◽  
Natural Evolution ◽  
Time To Market ◽  
Operational Costs ◽  
Network Provider ◽  
Network Functions ◽  
Cloud Technologies

Network functions virtualization (NFV) is consolidating as one of the base technologies for the design, deployment, and operation of network services. NFV can be seen as a natural evolution of the trend to cloud technologies in IT, and hence perceived as bringing them to the network provider environments. While this can be true for the simplest cases, focused on the IT services network providers rely on, the nature of network services raises unique requirements on the overall virtualization process. NFV aims to provide at the same time an opportunity to network providers, not only in reducing operational costs but also in bringing the promise of easing the development and activation of new services, thereby reducing their time-to-market and opening new approaches for service provisioning and operation, in general. In this chapter, the authors analyse these requirements and opportunities, reviewing the state of the art in this new way of dealing with network services. Also, the chapter presents some NFV deployments endorsed by some network operators and identifies some remaining challenges.

Network Functions Virtualization

2015 ◽  
pp. 383-408 ◽  
Author(s):  
Diego R. López ◽  
Pedro A. Aranda
Keyword(s):  
Current Trend ◽  
Network Services ◽  
Service Provisioning ◽  
It Services ◽  
New Paradigm ◽  
Current State ◽  
Operational Costs ◽  
Network Provider ◽  
Network Functions ◽  
Cloud Technologies

Network Functions Virtualization (NFV) has emerged as a new paradigm for designing, deploying and operating network services. It is a natural evolution of the current trend of applying cloud technologies to Information Technology (IT) services, bringing them to network provider environments. While this is true for the most simple use cases, focused on the IT services network providers rely on, the nature of network services and the physical anchors of network themselves impose additional, unique requirements on the virtualization process in this environment. At the same time, NFV provides an opportunity to network providers, reducing operational costs and bringing the promise of dramatically easing the development of new services, reducing their time-to-market, and opening new possibilities for service provisioning. This chapter analyses these requirements and opportunities and the challenges NFV brings to network providers, and reviews the current state of the art in this new way of dealing with network services.

scholarly journals Data-Efficient Sensor Upgrade Path Using Knowledge Distillation

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6523
Author(s):  
Pieter Van Van Molle ◽  
Cedric De De Boom ◽  
Tim Verbelen ◽  
Bert Vankeirsbilck ◽  
Jonas De De Vylder ◽  
...  
Keyword(s):  
Deep Neural Networks ◽  
State Of The Art ◽  
Original Data ◽  
Radar Data ◽  
Teacher Supervision ◽  
Multispectral Images ◽  
Test Set ◽  
Time To Market ◽  
Speed Up ◽  
Knowledge Distillation

Deep neural networks have achieved state-of-the-art performance in image classification. Due to this success, deep learning is now also being applied to other data modalities such as multispectral images, lidar and radar data. However, successfully training a deep neural network requires a large reddataset. Therefore, transitioning to a new sensor modality (e.g., from regular camera images to multispectral camera images) might result in a drop in performance, due to the limited availability of data in the new modality. This might hinder the adoption rate and time to market for new sensor technologies. In this paper, we present an approach to leverage the knowledge of a teacher network, that was trained using the original data modality, to improve the performance of a student network on a new data modality: a technique known in literature as knowledge distillation. By applying knowledge distillation to the problem of sensor transition, we can greatly speed up this process. We validate this approach using a multimodal version of the MNIST dataset. Especially when little data is available in the new modality (i.e., 10 images), training with additional teacher supervision results in increased performance, with the student network scoring a test set accuracy of 0.77, compared to an accuracy of 0.37 for the baseline. We also explore two extensions to the default method of knowledge distillation, which we evaluate on a multimodal version of the CIFAR-10 dataset: an annealing scheme for the hyperparameter α and selective knowledge distillation. Of these two, the first yields the best results. Choosing the optimal annealing scheme results in an increase in test set accuracy of 6%. Finally, we apply our method to the real-world use case of skin lesion classification.

scholarly journals SDN/NFV VNF Service Chaining

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Dashmeet Anand, Hariharakumar Narasimhakumar, Et al.
Keyword(s):  
Large Scale ◽  
Virtual Network ◽  
Network Services ◽  
Entire System ◽  
Performance Parameters ◽  
Cloud Environment ◽  
Network Resources ◽  
Service Chain ◽  
Network Functions ◽  
Multiple Network

Service Function Chaining (SFC) is a capability that links multiple network functions to deploy end-to-end network services. By virtualizing these network functions also known as Virtual Network Functions (VNFs), the dependency on traditional hardware can be removed, hence making it easier to deploy dynamic service chains over the cloud environment. Before implementing service chains over a large scale, it is necessary to understand the performance overhead created by each VNF owing to their varied characteristics. This research paper attempts to gain insights on the server and networking overhead encountered when a service chain is deployed on a cloud orchestration tool such as OpenStack. Specifically, this research will measure the CPU utilization, RAM usage and System Load of the server hosting OpenStack. Each VNF will be monitored for its varying performance parameters when subjected to different kinds of traffic. Our focus lies on acquiring performance parameters of the entire system for different service chains and compare throughput, latency, and VNF statistics of the virtual network. Insights obtained from this research can be used in the industry to achieve optimum performance of hardware and network resources while deploying service chains.

scholarly journals SNF: Synthesizing high performance NFV service chains

2016 ◽  
Author(s):  
Georgios P Katsikas ◽  
Marcel Enguehard ◽  
Maciej Kuźniar ◽  
Gerald Q Maguire Jr. ◽  
Dejan Kostić
Keyword(s):  
Set Theory ◽  
High Performance ◽  
State Of The Art ◽  
Cross Layer ◽  
Minimal Set ◽  
Internet Service ◽  
Service Chain ◽  
Network Function ◽  
Network Functions ◽  
Baseline State

In this paper we introduce SNF, a framework that synthesizes (S) network function (NF) service chains by eliminating redundant I/O and repeated elements, while consolidating stateful cross layer packet operations across the chain. SNF uses graph composition and set theory to determine traffic classes handled by a service chain composed of multiple elements. It then synthesizes each traffic class using a minimal set of new elements that apply single-read-single-write and early-discard operations. Our SNF prototype takes a baseline state-of-the-art network functions virtualization (NFV) framework to the level of performance required for practical NFV service deployments. Software-based SNF realizes long (up to 10 NFs) and stateful service chains that achieve line-rate 40 Gbps throughput (up to 8.5x greater than the baseline NFV framework). Hardware-assisted SNF, using a commodity OpenFlow switch, shows that our approach scales at 40 Gbps for Internet Service Provider-level NFV deployments.

Introducing Automation in Service Delivery Procedures

2015 ◽  
pp. 409-430
Author(s):  
Isabel Borges
Keyword(s):  
Information Technologies ◽  
High Volume ◽  
Resource Provisioning ◽  
Network Services ◽  
Network Nodes ◽  
Network Equipment ◽  
Standard Information ◽  
Network Functions ◽  
And Storage ◽  
Data Centres

The combination of Software-Defined Networking (SDN) with Network Functions Virtualization (NFV) approaches is gaining momentum in the Industry as a new way of implementing, managing and controlling telecommunications networks. This chapter aims to go through SDN and lightly over NFV, presenting main characteristics and the standardization work on that technologies. SDN enables programming networks together with the ability to adapt to applications requirements and network dynamics. NFV aims at virtualizing network services by merging several network equipment types onto standard Information Technologies (IT) high volume virtualization technology (switches, servers and storage) located either in data centres, customer premises or network nodes. SDN and NFV interworking ambition is to bring on-demand resource provisioning, resource elasticity, among others with a centralized view of the overall network, able to automatically and dynamically honor service requirements.

Generate and Test for Formulated Product Variants With Information Extraction and an In-Silico Model

2020 ◽  
pp. 223-250
Author(s):  
Sagar Sunkle ◽  
Deepak Jain ◽  
Krati Saxena ◽  
Ashwini Patil ◽  
Rinu Chacko ◽  
...  
Keyword(s):  
Information Extraction ◽  
Product Design ◽  
Chemical Industry ◽  
In Silico ◽  
State Of The Art ◽  
Graph Database ◽  
Extended Time ◽  
Time To Market ◽  
In Silico Model ◽  
Chemical Products

The chemical industry is expanding its focus from process-centered products to product-centered products. Of these, consumer chemical products and other similar formulated products are especially ubiquitous. State of the art in the formulated product design relies heavily on experts and their expertise, leading to extended time to market and increased costs. The authors show that it is possible to construct a graph database of various details of products from textual sources, both offline and online. Similar to the “generate and test” approach, they propose that it is possible to generate feasible design variants of a given type of formulated product using the database so constructed. If they restrict the set of products that are applied to the skin, they propose to test the generated design variants using an in-silico model. Even though this chapter is an account of the work in progress, the authors believe the gains they can obtain from a readily accessible database and its integration with an in-silico model are substantial.

Critical Logistics Support Enables Fast Track Construction for High Speed Rail

2010 ◽  
Author(s):  
James R. Blaze ◽  
Jay Gowan ◽  
Stephen Byers
Keyword(s):  
Construction Management ◽  
Construction Projects ◽  
High Speed ◽  
Fast Track ◽  
State Of The Art ◽  
Economic Advantage ◽  
High Speed Rail ◽  
Operational Costs ◽  
Construction Zones ◽  
Made In

Paper and PowerPoint presentation format will describe process for much faster logistics and construction management of new high speed track construction and improvement of existing FRA track from FRA Class 4 to Class 5 and Class 6 standards on existing freight railway lines. This process involves an integration of the long materials supply chain together with rapid process state of the art construction machines. These machines have been used in both European and Chinese high speed construction projects. Huge gains in new track kilometers and miles per day have been made in the last decade on the machinery side of the equation. The authors will show several case studies. The critical key to these production rates has been in the integration of materials ordering and prepositioning. The economic advantage is that track time construction windows that delay other passing trains can be reduced at tremendous savings in service and operational costs to the operators already providing service in these new high speed corridors and construction zones. Examples and calculations are shown.

scholarly journals Metron

2021 ◽  
Vol 38 (1-2) ◽  
pp. 1-45
Author(s):  
Georgios P. Katsikas ◽  
Tom Barbette ◽  
Dejan Kostić ◽  
JR. Gerald Q. Maguire ◽  
Rebecca Steinert
Keyword(s):  
Load Balancing ◽  
High Speed ◽  
State Of The Art ◽  
Single Server ◽  
Packet Processing ◽  
Commodity Hardware ◽  
Multiple Servers ◽  
Underlying Network ◽  
Network Functions

Deployment of 100Gigabit Ethernet (GbE) links challenges the packet processing limits of commodity hardware used for Network Functions Virtualization (NFV). Moreover, realizing chained network functions (i.e., service chains) necessitates the use of multiple CPU cores, or even multiple servers, to process packets from such high speed links. Our system Metron jointly exploits the underlying network and commodity servers’ resources: ( i ) to offload part of the packet processing logic to the network, ( ii )  by using smart tagging to setup and exploit the affinity of traffic classes, and ( iii )  by using tag-based hardware dispatching to carry out the remaining packet processing at the speed of the servers’ cores, with zero inter-core communication. Moreover, Metron transparently integrates, manages, and load balances proprietary “blackboxes” together with Metron service chains. Metron realizes stateful network functions at the speed of 100GbE network cards on a single server, while elastically and rapidly adapting to changing workload volumes. Our experiments demonstrate that Metron service chains can coexist with heterogeneous blackboxes, while still leveraging Metron’s accurate dispatching and load balancing. In summary, Metron has ( i )  2.75–8× better efficiency, up to ( ii )  4.7× lower latency, and ( iii )  7.8× higher throughput than OpenBox, a state-of-the-art NFV system.

scholarly journals Reconfigurable Network Stream Processing on Virtualized FPGA Resources

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qianqiao Chen ◽  
Vaibhawa Mishra ◽  
Jose Nunez-Yanez ◽  
Georgios Zervas
Keyword(s):  
General Purpose ◽  
Network Services ◽  
Network Function Virtualization ◽  
Network Function ◽  
Software Applications ◽  
Data Plane ◽  
High Bandwidth ◽  
Network Functions ◽  
Reconfigurable Platform ◽  
On Chip

The software defined network and network function virtualization are proposed to address the network ossification issue in current Internet infrastructure. Network functions and services are implemented as software applications to increase the programmability of network. However, involving general purpose processors in data plane restricts the bandwidth of network services. Therefore, to keep both the bandwidth and flexibility, a FPGA platform is suggested as a reconfigurable platform to deliver high bandwidth virtual network functions on data plane. In this paper, the FPGA resource has been virtualized by interconnecting partial reconfigurable regions to deliver high bandwidth reconfigurable processing on network streams. With the help of partial reconfiguration technology, network functions on our platform can be configured without affecting other functions on the same FPGA device. The on-chip interconnect system is further evaluated by comparing with existing network-on-chip system. A reconfiguration process is also proposed and demonstrated that it can be performed on our platform. The process can happen in the real time of network services and it is able to keep the original function working during the download of partial bitstream.

scholarly journals Improving the network traffic classification using the Packet Vision approach

2020 ◽  
Author(s):  
Rodrigo Moreira ◽  
Larissa Rodrigues ◽  
Pedro Rosa ◽  
Flávio Silva
Keyword(s):  
Mobile Networks ◽  
Network Traffic ◽  
State Of The Art ◽  
Security And Privacy ◽  
Network Services ◽  
Network Architectures ◽  
Traffic Classification ◽  
Raw Data ◽  
Network Traffic Classification ◽  
Application Aware

The network traffic classification allows improving the management, and the network services offer taking into account the kind of application. The future network architectures, mainly mobile networks, foresee intelligent mechanisms in their architectural frameworks to deliver application-aware network requirements. The potential of convolutional neural networks capabilities, widely exploited in several contexts, can be used in network traffic classification. Thus, it is necessary to develop methods based on the content of packets transforming it into a suitable input for CNN technologies. Hence, we implemented and evaluated the Packet Vision, a method capable of building images from packets raw-data, considering both header and payload. Our approach excels those found in state-of-the-art by delivering security and privacy by transforming the raw-data packet into images. Therefore, we built a dataset with four traffic classes evaluating the performance of three CNNs architectures: AlexNet, ResNet-18, and SqueezeNet. Experiments showcase the Packet Vision combined with CNNs applicability and suitability as a promising approach to deliver outstanding performance in classifying network traffic.

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