Network Function Virtualization Service Research Articles

Deep-Learning-Assisted Network Orchestration for On-Demand and Cost-Effective vNF Service Chaining in Inter-DC Elastic Optical Networks

This work addresses the relatively long setup latency and complicated network control and management caused by on-demand virtual network function service chain (vNF-SC) provisioning in inter-datacenter elastic optical networks. We first design a provisioning framework with resource pre-deployment to resolve the aforementioned challenge. Specifically, the framework is designed as a discrete-time system, in which the operations are performed periodically in fixed time slots (TS). Each TS includes a pre-deployment phase followed by a provisioning phase. In the pre-deployment phase, a deep-learning (DL) model is designed to predict future vNF-SC requests, then lightpath establishment and vNF deployment are performed accordingly to pre-deploy resources for the predicted requests. Then, the system proceeds to the provisioning phase, which collects dynamic vNF-SC requests from clients and serves them in real-time by steering their traffic through the required vNFs in sequence. In order to forecast the high-dimensional data of future vNF-SC requests accurately, we design our DL model based on the long/short-term memory-based neural network and develop an effective training scheme for it. Then, the provisioning framework and DL model are optimized from several perspectives. We evaluate our proposed framework with simulations that leverage real traffic traces. The results indicate that our DL model achieves higher request prediction accuracy and lower blocking probability than two benchmarks that also predict vNF-SC requests and follow the principle of the proposed provisioning framework.

Online Scaling of NFV Service Chains Across Geo-Distributed Datacenters

Network Function Virtualization (NFV) is an emerging paradigm that turns hardware-dependent implementation of network functions (i.e., middleboxes) into software modules running on virtualized platforms, for significant cost reduction and ease of management. Such virtual network functions (VNFs) commonly constitute service chains, to provide network services that traffic flows need to go through. Efficient deployment of VNFs for network service provisioning is key to realize the NFV goals. Existing efforts on VNF placement mostly deal with offline or one-time placement, ignoring the fundamental, dynamic deployment and scaling need of VNFs to handle practical time-varying traffic volumes. This work investigates dynamic placement of VNF service chains across geo-distributed datacenters to serve flows between dispersed source and destination pairs, for operational cost minimization of the service chain provider over the entire system span. An efficient online algorithm is proposed, which consists of two main components: (1) A regularization-based approach from online learning literature to convert the offline optimal deployment problem into a sequence of one-shot regularized problems, each to be efficiently solved in one time slot; (2) An online dependent rounding scheme to derive feasible integer solutions from the optimal fractional solutions of the one-shot problems, and to guarantee a good competitive ratio of the online algorithm over the entire time span. We verify our online algorithm with solid theoretical analysis and trace-driven simulations under realistic settings.

Leveraging Mixed-Strategy Gaming to Realize Incentive-Driven VNF Service Chain Provisioning in Broker-Based Elastic Optical Inter-Datacenter Networks

This paper investigates the problem of how to optimize the provisioning of virtual network function service chains (VNF-SCs) in elastic optical inter-datacenter networks (EO-IDCNs) under elastic optical networking and DC capacity constraints. We take advantage of the broker-based hierarchical control paradigm for the orchestration of cross-stratum resources and propose to realize incentive-driven VNF-SC provisioning with a noncooperative mixed-strategy gaming approach. The proposed gaming model enables tenants to compete for VNF-SC provisioning services due to revenue and quality-of-service incentives and therefore can motivate more reasonable selections of provisioning schemes. We detail the modeling of the game, discuss the existence of the Nash equilibrium states, and design an auxiliary graph-based heuristic algorithm for tenants to compute approximate equilibrium solutions in the games. A dynamic resource pricing strategy, which can set the prices of network resources in real time according to the actual network status, is also introduced for EO-IDCNs as a complementary method to the game-theoretic approach. Results from extensive simulations that consider both static network planning and dynamic service provisioning scenarios indicate that the proposed game-theoretic approach facilitates both higher tenant and network-wide profits and improves the network throughput as well compared with the baseline algorithms, while the dynamic pricing strategy can further reduce the request blocking probability with a factor of ∼2.4×.

On service-chaining strategies using Virtual Network Functions in operator networks

Network functions (e.g., firewalls, load balancers, etc.) have been traditionally provided through proprietary hardware appliances. Often, hardware appliances need to be hardwired back-to-back to form a service chain providing chained network functions. These hardware appliances cannot be provisioned on-demand since they are statically embedded in the network topology, making creation, insertion, modification, upgrade, and removal of service chains complex, and also slowing down service innovation. Hence, network operators are starting to deploy Virtual Network Functions (VNFs), which are virtualized over commodity hardware. VNFs can be deployed in Data Centers (DCs) or in Network Function Virtualization (NFV)-capable network elements (nodes) such as routers and switches. NFV-capable nodes and DCs together form a Network-enabled Cloud (NeC) that helps to facilitate the dynamic service chaining required to support today’s evolving network traffic and its service demands. In this study, we focus on the VNF service-chain placement and traffic routing problem, and build a model for placing a VNF service chain while minimizing network-resource consumption. Further, we study the network-resource consumption of various service-chaining strategies, which can be a NeC having a varying number of NFV-capable nodes or a proprietary hardware solution. Our results indicate that a NeC having a DC and NFV-capable nodes can significantly reduce network-resource consumption.

NFV Security Survey: From Use Case Driven Threat Analysis to State-of-the-Art Countermeasures

Network functions virtualization (NFV), along with software-defined networking (SDN), drives a new change in networking infrastructure with respect to designing, deploying, and managing various network services. In particular, NFV has potential to significantly reduce the hardware cost, greatly improve operational efficiency, and dramatically shorten the development lifecycle of network service. It also makes network functions and services much more adaptive and scalable. Despite the promising advantages of NFV, security remains to be one of the vital concerns and potential hurdle, as attack surface becomes unclear and defense line turns to be blurred in the virtualization environment. This survey is therefore devoted to analyzing NFV from a security perspective. We first analyze security threats of five well-defined NFV use cases, with an objective to establishing a comprehensive layer-specific threat taxonomy. Second, we conduct in-depth comparative studies on several security mechanisms that are applied in traditional scenarios and in NFV environments. The purpose is to analyze their implicit relationships with NFV performance objectives in terms of feasibility, agility, effectiveness, and so on. Third, based on the established threat taxonomy and the analyzed security mechanisms, we provide a set of recommendations on securing NFV based services, along with the analysis on the state-of-the-art security countermeasures. A resulting holistic security framework is intended to lay a foundation for NFV service providers to deploy adaptive, scalable, and cost-effective security hardening based on their particular needs. Some future research directions are finally discussed.

VirtPhy: Fully Programmable NFV Orchestration Architecture for Edge Data Centers

Emerging paradigms, such as edge computing, require the geographical distribution of small-scale data centers that will use network functions virtualization (NFV) to provide new services with stringent demands related to throughput, latency, cost, innovation, and efficient orchestration. To tackle these demands, this paper proposes VirtPhy, a fully programmable architecture for NFV orchestration in edge data centers, based on server-centric topologies, software-defined networking, software switches, distributed service chaining, and source routing. A proof-of-concept is implemented in a data center testbed using OpenStack cloud platform in a hypercube topology. The results show its orchestration mechanisms can efficiently provision NFV service requests by steering traffic through a sequence of virtualized network functions in a server-centric topology.

NFV-Throttle: An Overload Control Framework for Network Function Virtualization

Network function virtualization (NFV) aims to provide high-performance network services through cloud computing and virtualization technologies. However, network overloads represent a major challenge. While elastic cloud computing can partially address overloads by scaling on-demand, this mechanism is not quick enough to meet the strict high-availability requirements of “carrier-grade” telecom services. Thus, in this paper we propose a novel overload control framework (NFV-Throttle) to protect NFV services from failures due to an excess of traffic in the short term, by filtering the incoming traffic toward virtual network functions (VNFs) to make the best use of the available capacity, and to preserve the QoS of traffic flows admitted in the network. Moreover, the framework has been designed to fit the service models of NFV, including VNFaaS and NFVIaaS . We present an extensive experimental evaluation on the NFV-oriented Clearwater IMS, showing that the solution is robust and able to sustain severe overload conditions with a very small performance overhead.

T-NOVA: An Open-Source MANO Stack for NFV Infrastructures

One of the primary challenges associated with network functions virtualization (NFV) is the automated management of the service lifecycle. In this paper, we present a full software-based management and orchestration (MANO) stack which operates with OpenStack and OpenDaylight controllers and has the in-built functionality to automate the key phases of the NFV service lifecycle, namely resource discovery and matching, service mapping, service deployment, and monitoring. The MANO stack is being implemented by the EU FP7 project T-NOVA, with the components being released as open-source software. Service mapping and service deployment solutions developed in the scope of T-NOVA are presented in detail. As a proof-of-concept, we evaluate the performance of a virtualized traffic classifier network function, demonstrating the gains of virtualized hardware acceleration.

Online Stochastic Buy-Sell Mechanism for VNF Chains in the NFV Market

With the recent advent of network functions virtualization (NFV), enterprises and businesses are looking into network service provisioning through the service chains of virtual network functions (VNFs), instead of relying on dedicated hardware middleboxes. Accompanying this trend, an NFV market is emerging, where NFV service providers create VNF instances, assemble VNF service chains, and sell them for the use of customers, using resources (computing, bandwidth) that they own or rent from other resource suppliers. Efficient service chain provisioning and pricing mechanisms are still missing, to charge assembled service chains according to demand and the supply of resources at any time. We propose an online stochastic auction mechanism for on-demand service chain provisioning and pricing at an NFV provider. Our auction takes in buy bids for service chains from multiple customers and sell bids from various resource suppliers to supplement the NFV provider’s geo-distributed resource pool, with resource occupation/contribution durations. We extend online primal-dual optimization framework for handling both buyers and sellers, with a new competitive analysis. The online mechanism maximizes the expected social welfare of the NFV ecosystem (the NFV provider, customers and resource suppliers) with a good competitive ratio as compared with the expected offline optimal social welfare, while guaranteeing truthfulness in bidding, individual rationality for both buyers and sellers, and polynomial time for computation. We evaluate our mechanism through trace-driven simulation studies, and demonstrate a close-to-offline-optimal performance in expected social welfare under realistic settings.

Clustered NFV Service Chaining Optimization in Mobile Edge Clouds

Service chaining is one of the key technologies that is used to support mobile edge computing (MEC) services for users in mobile communications radio access networks (RANs). By adapting network functions virtualization (NFV) technology to MEC, cloud-computing functionalities can be allocated near the base station of the RAN, resulting in extremely fast service access to user equipment. This letter provides a clustered NFV service chaining (cNSC) scheme that computes the optimal number of clusters to minimize the end-to-end time of MEC services. The cNSC scheme is applied to form multiple MEC clusters of NFV enabled nodes within the RAN.

Profiling and accelerating commodity NFV service chains with SCC

Recent approaches to network functions virtualization (NFV) have shown that commodity network stacks and drivers struggle to keep up with increasing hardware speed. Despite this, popular cloud networking services still rely on commodity operating systems (OSs) and device drivers. Taking into account the hardware underlying of commodity servers, we built an NFV profiler that tracks the movement of packets across the system’s memory hierarchy by collecting key hardware and OS-level performance counters. Leveraging the profiler’s data, our Service Chain Coordinator’s (SCC) run-time accelerates user-space NFV service chains, based on commodity drivers. To do so, SCC combines multiplexing of system calls with scheduling strategies, taking time, priority, and processing load into account. By granting longer time quanta to chained network functions (NFs), combined with I/O multiplexing, SCC reduces unnecessary scheduling and I/O overheads, resulting in three-fold latency reduction due to cache and main memory utilization improvements. More importantly, SCC reduces the latency variance of NFV service chains by up to 40x compared to standard FastClick chains by making the average case for an NFV chain to perform as well as the best case. These improvements are possible because of our profiler’s accuracy.

SNF: synthesizing high performance NFV service chains

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.

Joint Spectrum and IT Resource Allocation for Efficient VNF Service Chaining in Inter-Datacenter Elastic Optical Networks

We study how to allocate spectrum and IT resources jointly for realizing efficient virtual network function (VNF) service chaining in inter-datacenter elastic optical networks. We first formulate an integer linear programming model to solve the problem exactly, and then a longest common subsequence-based heuristic is proposed. The simulation results indicate that the proposed algorithms can reuse the deployed VNFs efficiently and arrange the spectrum utilization in a much more load-balanced manner.