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 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.

scholarly journals NVP: A Network Virtualization Proxy for Software Defined Networking

2016 ◽  
Vol 11 (5) ◽  
pp. 697 ◽  
Author(s):  
Billy Pinheiro ◽  
Eduardo Cerqueira ◽  
Antonio Abelem
Keyword(s):  
Large Scale ◽  
Network Virtualization ◽  
Software Defined Networking ◽  
Network Function Virtualization ◽  
Load Testing ◽  
Proof Of Concept ◽  
Network Resources ◽  
Network Function ◽  
Large Scale Networks ◽  
Proper Solutions

The combination of Network Function Virtualization (NFV) and Software Defined Networking (SDN) can improve the control and utilization of network resources. However, this issue still requires proper solutions to virtualize large-scale networks, which would allow the use of SDN and Virtualization in real environments.Thus, this paper proposes a virtualization architecture for SDN that relies on a proxy-based approach. The NVP (Network Virtualization Proxy) is a virtualization proxy that intercepts messages exchanged between controllers and switches SDN enabling network virtualization. An implementation of the proposal was developed as a proof of concept and load testing was performed showing that the solution can provide network virtualization in a scalable manner, using less than 2.5 MB of memory to manage 100 switches performing simultaneous requests, whereas FlowVisor requires more than 200 MB.

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.

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.

scholarly journals Using Aerial and Vehicular NFV Infrastructures to Agilely Create Vertical Services

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1342
Author(s):  
Borja Nogales ◽  
Miguel Silva ◽  
Ivan Vidal ◽  
Miguel Luís ◽  
Francisco Valera ◽  
...  
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc ◽  
Cost Effective ◽  
Network Services ◽  
Network Function Virtualization ◽  
Mobile Environments ◽  
Network Resources ◽  
The Public ◽  
Network Function ◽  
And Performance

5G communications have become an enabler for the creation of new and more complex networking scenarios, bringing together different vertical ecosystems. Such behavior has been fostered by the network function virtualization (NFV) concept, where the orchestration and virtualization capabilities allow the possibility of dynamically supplying network resources according to its needs. Nevertheless, the integration and performance of heterogeneous network environments, each one supported by a different provider, and with specific characteristics and requirements, in a single NFV framework is not straightforward. In this work we propose an NFV-based framework capable of supporting the flexible, cost-effective deployment of vertical services, through the integration of two distinguished mobile environments and their networks: small sized unmanned aerial vehicles (SUAVs), supporting a flying ad hoc network (FANET) and vehicles, promoting a vehicular ad hoc network (VANET). In this context, a use case involving the public safety vertical will be used as an illustrative example to showcase the potential of this framework. This work also includes the technical implementation details of the framework proposed, allowing to analyse and discuss the delays on the network services deployment process. The results show that the deployment times can be significantly reduced through a distributed VNF configuration function based on the publish–subscribe model.

scholarly journals On Blockchain-Based Cross-Service Communication and Resource Orchestration on Edge Clouds

Informatics ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 13
Author(s):  
Konstantinos Papadakis-Vlachopapadopoulos ◽  
Ioannis Dimolitsas ◽  
Dimitrios Dechouniotis ◽  
Eirini Eleni Tsiropoulou ◽  
Ioanna Roussaki ◽  
...  
Keyword(s):  
Network Function Virtualization ◽  
Network Resources ◽  
Service Orchestration ◽  
Network Slicing ◽  
Network Function ◽  
Resource Orchestration ◽  
Full Capacity ◽  
Cloud Datacenter ◽  
Set Up ◽  
The Internet Of Things

With the advent of 5G verticals and the Internet of Things paradigm, Edge Computing has emerged as the most dominant service delivery architecture, placing augmented computing resources in the proximity of end users. The resource orchestration of edge clouds relies on the concept of network slicing, which provides logically isolated computing and network resources. However, though there is significant progress on the automation of the resource orchestration within a single cloud or edge cloud datacenter, the orchestration of multi-domain infrastructure or multi-administrative domain is still an open challenge. Towards exploiting the network service marketplace at its full capacity, while being aligned with ETSI Network Function Virtualization architecture, this article proposes a novel Blockchain-based service orchestrator that leverages the automation capabilities of smart contracts to establish cross-service communication between network slices of different tenants. In particular, we introduce a multi-tier architecture of a Blockchain-based network marketplace, and design the lifecycle of the cross-service orchestration. For the evaluation of the proposed approach, we set up cross-service communication in an edge cloud and we demonstrate that the orchestration overhead is less than other cross-service solutions.

scholarly journals Low-complexity sparse-aware multiuser detection for large-scale MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rong Ran ◽  
Hayoung Oh
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Finite Alphabet ◽  
Multiuser Detectors ◽  
Input Multiple Output ◽  
Error Detector ◽  
Significant Performance

AbstractSparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors.

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