scholarly journals Virtual Network Function Embedding under Nodal Outage Using Deep Q-Learning

2021 ◽  
Vol 13 (3) ◽  
pp. 82
Author(s):  
Swarna Bindu Chetty ◽  
Hamed Ahmadi ◽  
Sachin Sharma ◽  
Avishek Nag
Keyword(s):  
Communication Networks ◽  
Dynamic Network ◽  
Computation Time ◽  
Failure Recovery ◽  
Network Function Virtualization ◽  
Q Learning ◽  
Network Function ◽  
Critical Issues ◽  
Experience Replay ◽  
Network Functions

With the emergence of various types of applications such as delay-sensitive applications, future communication networks are expected to be increasingly complex and dynamic. Network Function Virtualization (NFV) provides the necessary support towards efficient management of such complex networks, by virtualizing network functions and placing them on shared commodity servers. However, one of the critical issues in NFV is the resource allocation for the highly complex services; moreover, this problem is classified as an NP-Hard problem. To solve this problem, our work investigates the potential of Deep Reinforcement Learning (DRL) as a swift yet accurate approach (as compared to integer linear programming) for deploying Virtualized Network Functions (VNFs) under several Quality-of-Service (QoS) constraints such as latency, memory, CPU, and failure recovery requirements. More importantly, the failure recovery requirements are focused on the node-outage problem where outage can be either due to a disaster or unavailability of network topology information (e.g., due to proprietary and ownership issues). In DRL, we adopt a Deep Q-Learning (DQL) based algorithm where the primary network estimates the action-value function Q, as well as the predicted Q, highly causing divergence in Q-value’s updates. This divergence increases for the larger-scale action and state-space causing inconsistency in learning, resulting in an inaccurate output. Thus, to overcome this divergence, our work has adopted a well-known approach, i.e., introducing Target Neural Networks and Experience Replay algorithms in DQL. The constructed model is simulated for two real network topologies—Netrail Topology and BtEurope Topology—with various capacities of the nodes (e.g., CPU core, VNFs per Core), links (e.g., bandwidth and latency), several VNF Forwarding Graph (VNF-FG) complexities, and different degrees of the nodal outage from 0% to 50%. We can conclude from our work that, with the increase in network density or nodal capacity or VNF-FG’s complexity, the model took extremely high computation time to execute the desirable results. Moreover, with the rise in complexity of the VNF-FG, the resources decline much faster. In terms of the nodal outage, our model provided almost 70–90% Service Acceptance Rate (SAR) even with a 50% nodal outage for certain combinations of scenarios.

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.

ONAP

2021 ◽  
pp. 212-249
Author(s):  
Eric Debeau ◽  
Veronica Quintuna-Rodriguez
Keyword(s):  
Network Function Virtualization ◽  
Network Function ◽  
On Demand ◽  
Public Networks ◽  
5G Network ◽  
Network Flexibility ◽  
Optimal Resource ◽  
Network Functions ◽  
Lifecycle Management ◽  
Automation Techniques

The ever-increasing complexity of networks and services advocates for the introduction of automation techniques to facilitate the design, the delivery, and the operation of such networks and services. The emergence of both network function virtualization (NFV) and software-defined networks (SDN) enable network flexibility and adaptability which open the door to on-demand services requiring automation. In aim of holding the increasing number of customized services and the evolved capabilities of public networks, the open network automation platform (ONAP), which is in open source, particularly addresses automation techniques while enabling dynamic orchestration, optimal resource allocation capabilities, and end-to-end service lifecycle management. This chapter addresses the key ONAP features that can be used by industrials and operators to automatically manage and orchestrate a wide set of services ranging from elementary network functions (e.g., firewalls) to more complex services (e.g., 5G network slices).

scholarly journals VNF Placement Optimization at the Edge and Cloud †

2019 ◽  
Vol 11 (3) ◽  
pp. 69 ◽  
Author(s):  
Aris Leivadeas ◽  
George Kesidis ◽  
Mohamed Ibnkahla ◽  
Ioannis Lambadaris
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Research Area ◽  
End Users ◽  
Network Function Virtualization ◽  
Future Research ◽  
Cloud Infrastructure ◽  
Network Function ◽  
Computing Paradigm ◽  
Network Functions

Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions to enterprise customers and end-users remote from their premises. NFV along with Cloud Computing has also started to be seen in Internet of Things (IoT) platforms as a means to provide networking functions to the IoT traffic. The intermix of IoT, NFV, and Cloud technologies, however, is still in its infancy creating a rich and open future research area. To this end, in this paper, we propose a novel approach to facilitate the placement and deployment of service chained VNFs in a network cloud infrastructure that can be extended using the Mobile Edge Computing (MEC) infrastructure for accommodating mission critical and delay sensitive traffic. Our aim is to minimize the end-to-end communication delay while keeping the overall deployment cost to minimum. Results reveal that the proposed approach can significantly reduce the delay experienced, while satisfying the Service Providers’ goal of low deployment costs.

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 Securing Virtual Network Function (VNF) in Telco Cloud

2020 ◽  
Author(s):  
Bharathkumar Ravichandran
Keyword(s):  
General Purpose ◽  
Virtual Network ◽  
Network Function Virtualization ◽  
Communication Architecture ◽  
Network Function ◽  
Fifth Generation ◽  
Security Challenges ◽  
5G Network ◽  
Network Functions ◽  
Computing Platforms

In the fifth generation mobile communication architecture (5G), network functions which traditionally existed as discrete hardware entities based on custom architectures, are replaced with dynamic, scalable Virtual Network Functions (VNF) that run on general purpose (x86) cloud computing platforms, under the paradigm Network Function Virtualization (NFV). The shift towards a virtualized infrastructure poses its own set of security challenges that need to be addressed. One such challenge that we seek to address in this paper is providing integrity, authenticity and confidentiality protection for VNFs.

scholarly journals Network Function Virtualization in Content-Centric Networks

2019 ◽  
Author(s):  
José Castillo-Lema ◽  
Augusto José Venâncio Neto ◽  
Flavio de Oliveira Silva ◽  
Sergio Takeo Kofuji
Keyword(s):  
Ip Networks ◽  
General Purpose ◽  
Virtual Network ◽  
Network Function Virtualization ◽  
Network Function ◽  
The Past ◽  
Central Controller ◽  
Network Functions ◽  
Extensive Effort ◽  
Hardware Platforms

Network Functions Virtualization (NFV) offers an alternative way to design, deploy, and manage networking functions and services by leveraging virtualization technologies to consolidate network functions into general-purpose hardware platforms. On the past years extensive effort has been made to evolve and mature NFV tecnologies over IP networks. However, little or no attempts at all have been made to incorporate NFV into Information-Centric Networks (ICN). This work explores the use and implementation of virtual Network Funtions (VNFS)in Content-Centric Networks (CCN), and proposes the use of the Named Function Networking (NFN) paradigm as means to implement network functions and services in this kind of networks, distributing the network functions and services through the networks nodes and providing flexibility to dynamically place functions in the network as required and without the need of a central controller.

scholarly journals Learning to Harness Bandwidth with Multipath Congestion Control and Scheduling

2021 ◽  
Author(s):  
Shiva Raj Pokhrel ◽  
Anwar Walid
Keyword(s):  
Congestion Control ◽  
Communication Networks ◽  
Packet Scheduling ◽  
Short Term Memory ◽  
Available Bandwidth ◽  
Network Characteristics ◽  
Q Learning ◽  
Multipath Tcp ◽  
Wireline Communication ◽  
Experience Replay

Multipath TCP (MPTCP) has emerged as a facilitator for harnessing and pooling available bandwidth in wireless/wireline communication networks and in data centers. Existing implementations of MPTCP such as, Linked Increase Algorithm (LIA), Opportunistic LIA (OLIA) and BAlanced LInked Adaptation (BALIA) include separate algorithms for congestion control and packet scheduling, with pre-selected control parameters. We propose a Deep Q-Learning (DQL) based framework for joint congestion control and packet scheduling for MPTCP. At the heart of the solution is an intelligent agent for interface, learning and actuation, which learns from experience optimal congestion control and scheduling mechanism using DQL techniques with policy gradients. We provide a rigorous stability analysis of system dynamics which provides important practical design insights. In addition, the proposed DQL-MPTCPalgorithm utilizes the ‘recurrent neural network’ and integrates it with ‘long short-term memory’ for continuously i) learning dynamic behavior of subflows (paths) and ii) responding promptly to their behavior using prioritized experience replay. With extensive emulations, we show that the proposed DQL-based MPTCP algorithm outperforms MPTCP LIA, OLIA and BALIA algorithms. Moreover, the DQL-MPTCP algorithm is robust to time-varying network characteristics and provides dynamic exploration and exploitation of paths. The revised version is to appear in IEEE Trans. in Mobile Computing soon.<br>

scholarly journals Machine-Learning Defined Networking: Towards Intelligent Networks

2021 ◽  
pp. 3-12
Author(s):  
Sebastian Troia
Keyword(s):  
Machine Learning ◽  
Service Providers ◽  
Dynamic Network ◽  
Network Function Virtualization ◽  
Traffic Demand ◽  
Network Function ◽  
Network Utilization ◽  
Underlying Network ◽  
Network Operations ◽  
Network Technologies

AbstractWith the advent of 5G technology and an ever-increasing traffic demand, today Communication Service Providers (CSPs) experience a progressive congestion of their networks. The operational complexity, the use of manual configuration, the static nature of current technologies together with fast-changing traffic profiles lead to: inefficient network utilization, over-provisioning of resources and very high Capital Expenditures (CapEx) and Operational Expenses (OpEx). This situation is forcing the CSPs to change their underlying network technologies, and have started to look at new technological solutions that increase the level of programmability, control, and flexibility of configuration, while reducing the overall costs related to network operations. Software Define Networking (SDN), Network Function Virtualization (NFV) and Machine Learning (ML) are accepted as effective solutions to reduce CapEx and OpEx and to boost network innovation. This chapter summarizes the content of my Ph.D. thesis, by presenting new ML-based approaches in order to efficiently optimize resources in 5G metro-core SDN/NFV networks. The main goal is to provide the modern CSP with intelligent and dynamic network optimization tools in order to address the requirements of increasing traffic demand and 5G technology.

scholarly journals An Availability-Enhanced Service Function Chain Placement Scheme in Network Function Virtualization

2019 ◽  
Vol 8 (2) ◽  
pp. 34
Author(s):  
Yansen Xu ◽  
Ved P. Kafle
Keyword(s):  
Single Point ◽  
Computation Time ◽  
Network Services ◽  
Network Function Virtualization ◽  
Placement Problem ◽  
Service Function ◽  
Network Function ◽  
Multiple Substrate ◽  
Service Function Chain ◽  
End To End

A service function chain (SFC) is an ordered virtual network function (VNF) chain for processing traffic flows to deliver end-to-end network services in a virtual networking environment. A challenging problem for an SFC in this context is to determine where to deploy VNFs and how to route traffic between VNFs of an SFC on a substrate network. In this paper, we formulate an SFC placement problem as an integer linear programing (ILP) model, and propose an availability-enhanced VNF placing scheme based on the layered graphs approach. To improve the availability of SFC deployment, our scheme distributes VNFs of an SFC to multiple substrate nodes to avoid a single point of failure. We conduct numerical analysis and computer simulation to validate the feasibility of our SFC scheme. The results show that the proposed scheme outperforms well in different network scenarios in terms of end-to-end delay of the SFC and computation time cost.

scholarly journals Path Mapping Approach for Network Function Virtualization Resource Allocation with Network Function Decomposition Support

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1173 ◽  
Author(s):  
Basheer Raddwan ◽  
Khalil AL-Wagih ◽  
Ibrahim A. Al-Baltah ◽  
Mohamed A. Alrshah ◽  
Mohammed A. Al-Maqri
Keyword(s):  
Resource Allocation ◽  
Execution Time ◽  
Service Providers ◽  
Virtual Network ◽  
Network Function Virtualization ◽  
Network Function ◽  
Function Decomposition ◽  
Mapping Approach ◽  
Network Functions ◽  
The Impact

Recently, Network Function Virtualization (NFV) and Software Defined Networking (SDN) have attracted many mobile operators. For the flexible deployment of Network Functions (NFs) in an NFV environment, NF decompositions and control/user plane separation have been introduced in the literature. That is to map traditional functions into their corresponding Virtual Network Functions (VNFs). This mapping requires the NFV Resource Allocation (NFV-RA) for multi-path service graphs with a high number of virtual nodes and links, which is a complex NP-hard problem that inherited its complexity from the Virtual Network Embedding (VNE). This paper proposes a new path mapping approach to solving the NFV-RA problem for decomposed Network Service Chains (NSCs). The proposed solution has symmetrically considered optimizing an average embedding cost with an enhancement on average execution time. The proposed approach has been compared to two other existing schemes using 6 and 16 scenarios of short and long simulation runs, respectively. The impact of the number of nodes, links and paths of the service requests on the proposed scheme has been studied by solving more than 122,000 service requests. The proposed Integer Linear Programming (ILP) and heuristic schemes have reduced the execution time up to 39.58% and 6.42% compared to existing ILP and heuristic schemes, respectively. Moreover, the proposed schemes have also reduced the average embedding cost and increased the profit for the service providers.

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