scholarly journals Cost-Efficient Resource Allocation Method for Heterogeneous Cloud Environments

2018 ◽  
pp. 15-21
Author(s):  
Marton Szabo ◽  
David Hajay ◽  
Mark Szalayz
Keyword(s):  
Network Architecture ◽  
Optimal Solution ◽  
Network Function Virtualization ◽  
Reference Network ◽  
Cloud Provider ◽  
Test Environment ◽  
Network Function ◽  
Efficient Resource ◽  
Amazon Web Services ◽  
Heterogeneous Cloud

In this paper we present a novel on-line NFV (Network Function Virtualization) orchestration algorithm for edge computing infrastructure providers that operate in a heterogeneous cloud environment. The goal of our algorithm is to minimize the usage of computing resources which are offered by a public cloud provider (e.g., Amazon Web Services), while fulfilling the required networking related constraints (latency, bandwidth) of the services to be deployed.We propose a reference network architecture which acts as a test environment for the evaluation of our algorithm. During the measurements, we compare our results to the optimal solution provided by an ILP-based solver.

NFV Practical Implementation

2018 ◽  
pp. 175-194
Author(s):  
Lalit Pandey
Keyword(s):  
Network Architecture ◽  
Software Implementation ◽  
Virtual Network ◽  
Network Function Virtualization ◽  
Practical Implementation ◽  
Network Function ◽  
Network Functions

This chapter is focused on the traditional network architecture limitations with NFV benefits. Discussion of NFV architecture and framework as well as management and orchestration has been discussed in this chapter. Cisco VNF portfolio and virtual network functions implementation is included with software implementation of the architecture of NFV (network function virtualization). Management and orchestration functional layers as per ETSI standard. The challenges in NFV implementation is also a concern today, which is a part of this chapter.

scholarly journals FaaM: FPGA-as-a-Microservice - A Case Study for Data Compression

2019 ◽  
Vol 214 ◽  
pp. 07029
Author(s):  
David Ojika ◽  
Ann Gordon-Ross ◽  
Herman Lam ◽  
Bhavesh Patel
Keyword(s):  
High Performance ◽  
Network Function Virtualization ◽  
Communication Overhead ◽  
Network Function ◽  
Gate Arrays ◽  
Emerging Trends ◽  
Field Programmable ◽  
Amazon Web Services ◽  
Programmable Gate Arrays

Field-programmable gate arrays (FPGAs) have largely been used in communication and high-performance computing and given the recent advances in big data and emerging trends in cloud computing (e.g., serverless [18]), FPGAs are increasingly being introduced into these domains (e.g., Microsoft’s datacenters [6] and Amazon Web Services [10]). To address these domains’ processing needs, recent research has focused on using FPGAs to accelerate workloads, ranging from analytics and machine learning to databases and network function virtualization. In this paper, we present an ongoing effort to realize a high-performance FPGA-as-a-microservice (FaaM) architecture for the cloud. We discuss some of the technical challenges and propose several solutions for efficiently integrating FPGAs into virtualized environments. Our case study deploying a multithreaded, multi-user compression as a microservice using the FaaM architecture indicate that microservices-based FPGA acceleration can sustain high-performance compared to straightforward implementation with minimal to no communication overhead despite the hardware abstraction.

scholarly journals Dynamic Spectrum Management with Network Function Virtualization for UAV Communication

2021 ◽  
Vol 101 (2) ◽  
Author(s):  
Zhengjia Xu ◽  
Ivan Petrunin ◽  
Antonios Tsourdos
Keyword(s):  
Urban Areas ◽  
Network Architecture ◽  
Communication Technologies ◽  
Spectrum Management ◽  
Dynamic Spectrum ◽  
Network Function Virtualization ◽  
Future Research ◽  
Dynamic Spectrum Management ◽  
Network Function ◽  
High Level

AbstractRapid 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.

scholarly journals Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks

2021 ◽  
Vol 11 (22) ◽  
pp. 10547
Author(s):  
Marios Gatzianas ◽  
Agapi Mesodiakaki ◽  
George Kalfas ◽  
Nikos Pleros ◽  
Francesca Moscatelli ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Network Function Virtualization ◽  
User Association ◽  
Computational Resource ◽  
Mixed Integer Linear Program ◽  
Resource Allocation Algorithm ◽  
Network Function

In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the traditional problems of user association and traffic routing, Virtual Network Function (VNF) placement needs to be jointly considered. To that end, in this paper, we focus on the joint network and computational resource allocation, targeting low network power consumption while satisfying the Service Function Chain (SFC), throughput, and delay requirements. Unlike the State-of-the-Art (SoA), we also take into account the Access Network (AN), while formulating the problem as a general Mixed Integer Linear Program (MILP). Due to the high complexity of the proposed optimal solution, we also propose a low-complexity energy-efficient resource allocation algorithm, which was shown to significantly outperform the SoA, by achieving up to 78% of the optimal energy efficiency with up to 742 times lower complexity. Finally, we describe an Orchestration Framework for the automated orchestration of vertical-driven services in Network Slices and describe how it encompasses the proposed algorithm towards optimized provisioning of heterogeneous computation and network resources across multiple network segments.

Virtualizing Network Functions in Software-Defined Networks

2018 ◽  
pp. 26-51 ◽  
Author(s):  
Vishal Kaushik ◽  
Ajay Sharma ◽  
Ravi Tomar
Keyword(s):  
Dynamic Behavior ◽  
Network Architecture ◽  
Software Defined Networking ◽  
Network Function Virtualization ◽  
Software Defined Networks ◽  
Network Behavior ◽  
Scalable Computing ◽  
Network Function ◽  
Pros And Cons ◽  
Network Functions

Software-defined networking (SDN) is an emerging network architecture that facilitates the network administrator to control and manage network behavior dynamically. Different from traditional networks, software-defined networks support dynamic and scalable computing. The dynamic behavior is achieved by decoupling or disassociating the system. The swing of control from tightly bound individual networks to assessable computing devices enables infrastructure abstraction. Due to the abstraction, the network can be considered as a logical or virtual entity. In this chapter, relation between network function virtualization (NFV) and software-defined networking (SDN) has been outlined. This chapter focuses on describing the pros and cons of NFV technologies. network functions virtualization (NFV) was founded under the work of the European Telecommunications Standards Institute (ETSI).

scholarly journals Resource Allocation in 4G and 5G Networks: A Review

2021 ◽  
Vol 13 (3) ◽  
Author(s):  
Lavanya-Nehan Degambur ◽  
Avinash Mungur ◽  
Sheeba Armoogum ◽  
Sameerchand Pudaruth
Keyword(s):  
Resource Allocation ◽  
Network Architecture ◽  
Electrical Energy ◽  
Network Function Virtualization ◽  
Network Architectures ◽  
5G Networks ◽  
Memory Space ◽  
Network Function ◽  
5G Network ◽  
End To End

The advent of 4G and 5G broadband wireless networks brings several challenges with respect to resource allocation in the networks. In an interconnected network of wireless devices, users, and devices, all compete for scarce resources which further emphasizes the fair and efficient allocation of those resources for the proper functioning of the networks. The purpose of this study is to discover the different factors that are involved in resource allocation in 4G and 5G networks. The methodology used was an empirical study using qualitative techniques by performing literature reviews on the state of art in 4G and 5G networks, analyze their respective architectures and resource allocation mechanisms, discover parameters, criteria and provide recommendations. It was observed that resource allocation is primarily done with radio resource in 4G and 5G networks, owing to their wireless nature, and resource allocation is measured in terms of delay, fairness, packet loss ratio, spectral efficiency, and throughput. Minimal consideration is given to other resources along the end-to-end 4G and 5G network architectures. This paper defines more types of resources, such as electrical energy, processor cycles and memory space, along end-to-end architectures, whose allocation processes need to be emphasized owing to the inclusion of software defined networking and network function virtualization in 5G network architectures. Thus, more criteria, such as electrical energy usage, processor cycle, and memory to evaluate resource allocation have been proposed.  Finally, ten recommendations have been made to enhance resource allocation along the whole 5G network architecture.

scholarly journals AMF Optimal Placement based on Deep Reinforcement Learning in Heterogeneous Radio Access Network

2020 ◽  
Author(s):  
hao jin ◽  
Wenzhe Pang ◽  
Chenglin Zhao
Keyword(s):  
Reinforcement Learning ◽  
Mobility Management ◽  
Network Architecture ◽  
Access Network ◽  
Optimal Placement ◽  
Network Function Virtualization ◽  
User Mobility ◽  
Radio Access Network ◽  
Network Function ◽  
Radio Access

Abstract To support various service requirements such as massive Machine Type Communications, Ultra-Reliable and Low-Latency Communications in 5G scenario, Network Function Virtualization (NFV) plays an important role in the 5G network architecture to manage and orchestrate network services. As the key network function responsible for mobility management, Access and Mobility Management Function (AMF) can be deployed flexibly at the edge of the radio access network to improve the performance of mobility management based on NFV. In this paper, the optimal placement of AMF is addressed based on Deep Reinforcement Learning (DRL) in a heterogeneous radio access network, which aims to minimize the network utility including the average delay of mobility management requests at AMF, the average wired hops to relay the requests and the cost of AMF instances. By considering time-varying features including user mobility and the arrival rate of user mobility management requests, an AMF optimal placement approach is proposed for the long term optimization. Simulation results show that the performance of the proposed DRL based AMF optimal placement approach outperforms that of the baselines.

scholarly journals Optimizing Traffic Engineering for Resilient Services in NFV-Based Connected Autonomous Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8446
Author(s):  
Tuan-Minh Pham ◽  
Thi-Minh Nguyen
Keyword(s):  
Traffic Engineering ◽  
Autonomous Vehicles ◽  
Large Scale ◽  
Optimal Solution ◽  
Network Function Virtualization ◽  
Approximation Solution ◽  
Network Function ◽  
Significant Performance ◽  
Service Disruption ◽  
Cloud Servers

The massive amount of data generated daily by various sensors equipped with connected autonomous vehicles (CAVs) can lead to a significant performance issue of data processing and transfer. Network Function Virtualization (NFV) is a promising approach to improving the performance of a CAV system. In an NFV framework, Virtual Network Function (VNF) instances can be placed in edge and cloud servers and connected together to enable a flexible CAV service with low latency. However, protecting a service function chain composed of several VNFs from a failure is challenging in an NFV-based CAV system (VCAV). We propose an integer linear programming (ILP) model and two approximation algorithms for resilient services to minimize the service disruption cost in a VCAV system when a failure occurs. The ILP model, referred to as TERO, allows us to obtain the optimal solution for traffic engineering, including the VNF placement and routing for resilient services with regard to dynamic routing. Our proposed algorithms based on heuristics (i.e., TERH) and reinforcement learning (i.e., TERA) provide an approximation solution for resilient services in a large-scale VCAV system. Evaluation results with real datasets and generated network topologies show that TERH and TERA can provide a solution close to the optimal result. It also suggests that TERA should be used in a highly dynamic VCAV system.

scholarly journals Energy Efficiency Opposition-Based Learning and Brain Storm Optimization for VNF-SC Deployment in IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hejun Xuan ◽  
Xuelin Zhao ◽  
Zhenghui Liu ◽  
Jianwei Fan ◽  
Yanling Li
Keyword(s):  
Energy Consumption ◽  
Optimal Solution ◽  
Network Function Virtualization ◽  
Simulation Experiments ◽  
Important Indicator ◽  
Service Chain ◽  
Network Function ◽  
Opposition Based Learning ◽  
The Internet Of Things ◽  
Virtual Network Function

Network Function Virtualization (NFV) can provide the resource according to the request and can improve the flexibility of the network. It has become the key technology of the Internet of Things (IoT). Resource scheduling for the virtual network function service chain (VNF-SC) is the key issue of the NFV. Energy consumption is an important indicator for the IoT; we take the energy consumption into the objective and define a novel objective to satisfying different objectives of the decision-maker. Due to the complexity of VNF-SC deployment problem, through taking into consideration of the heterogeneity of nodes (each node only can provide some specific VNFs), and the limitation of resources in each node, a novel optimal model is constructed to define the problem of VNF-SC deployment problem. To solve the optimization model effectively, a weighted center opposition-based learning is introduced to brainstorm optimization to find the optimal solution (OBLBSO). To show the efficiency of the proposed algorithm, numerous of simulation experiments have been conducted. Experimental results indicate that OBLBSO can improve the accuracy of the solution than compared algorithm.

An overview of the 5G mobile network architecture

2018 ◽  
Author(s):  
Phanidra Palagummi ◽  
Vedant Somani ◽  
Krishna M. Sivalingam ◽  
Balaji Venkat
Keyword(s):  
Wireless Network ◽  
Mobile Networks ◽  
Network Architecture ◽  
Mobile Network ◽  
Communication Technologies ◽  
Future Generation ◽  
Network Function Virtualization ◽  
Low Latency ◽  
High Bandwidth ◽  
Network Technologies

Networking connectivity is increasingly based on wireless network technologies, especially in developing nations where the wired network infrastructure is not accessible to a large segment of the population. Wireless data network technologies based on 2G and 3G are quite common globally; 4G-based deployments are on the rise during the past few years. At the same time, the increasing high-bandwidth and low-latency requirements of mobile applications has propelled the Third Generation Partnership Project (3GPP) standards organization to develop standards for the next generation of mobile networks, based on recent advances in wireless communication technologies. This standard is called the Fifth Generation (5G) wireless network standard. This paper presents a high-level overview of the important architectural components, of the advanced communication technologies, of the advanced networking technologies such as Network Function Virtualization and other important aspects that are part of the 5G network standards. The paper also describes some of the common future generation applications that require low-latency and high-bandwidth communications.

Sign in / Sign up

Export Citation Format

Share Document