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A Disaggregated Packet Processing Architecture for network function virtualization

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2020年第6期38卷 1075-1088页

作者： Chowdhury, Shihabur Rahman Anthony Bian, Haibo Bai, Tim Boutaba, Raouf Univ Waterloo David R Cheriton Sch Comp Sci Waterloo ON N2L 3G1 Canada Huawei Technol Canada Markham ON L3R 5A4 Canada Bioinformat Solut Inc Waterloo ON N2L 6J2 Canada Desire2Learn Canada Kitchener ON N2G 1H6 Canada

network function virtualization (NFV) promises to reduce the capital and operational expenditure for network operators by moving packet processing from purpose-built hardware to software running on commodity servers. However, the state-of-the-art in NFV is merely replacing monolithic hardware with monolithic Virtual network functions (VNFs), i.e., software that realizes different network functions. This is a good first step towards transitioning to NFV, however, common functionality is repeatedly implemented in monolithic VNFs. Repeated execution of such redundant functionality is particularly common when VNFs are chained to realize Service function Chains (SFCs) and results in wasted infrastructure resources. This stresses the need for re-architecting the NFV ecosystem, through modular VNF design and flexible service composition. From this perspective, we propose MicroNF (mu NF in short), a disaggregated packet processing architecture facilitating the deployment of VNFs and SFCs using reusable, loosely-coupled, and independently deployable components. We have implemented the proposed system, including the different architecture components and optimizations for improving packet processing throughput and latency. Extensive experiments on a testbed demonstrate that: (i) compared to monolithic VNF based SFCs, those composed of mu NFs achieve the same packet processing throughput while using less CPU cycles per packet on average;and (ii) mu NF-based SFCs can sustain the same packet processing throughput as those based on state-of-the-art run-to-completion VNF architecture while using lesser number of CPU cores.

关键词： Task analysis Resource management Computer architecture Hardware Software Noise measurement Middleboxes network function virtualization microservices middleboxes virtual network function decomposition

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Energy-Efficient Provisioning for Service function Chains to Support Delay-Sensitive Applications in network function virtualization

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IEEE INTERNET OF THINGS JOURNAL 2020年第7期7卷 6116-6131页

作者： Sun, Gang Zhou, Run Sun, Jian Yu, Hongfang Vasilakos, Athanasios V. Univ Elect Sci & Technol China Key Lab Opt Fiber Sensing & Commun Minist Educ Chengdu 611731 Peoples R China Peng Cheng Lab Shenzhen 518066 Peoples R China Fuzhou Univ Dept Comp Sci & Technol Fuzhou 350116 Peoples R China Lulea Univ Technol Dept Comp Sci Elect & Space Engn S-97187 Lulea Sweden

The efficient deployment of virtual network functions (VNFs) for network service provisioning is key for achieving network function virtualization (NFV);however, most existing studies address only offline or one-off deployments of service function chains (SFCs) while neglecting the dynamic (i.e., online) deployment and expansion requirements. In particular, many methods of energy/resource cost reduction are achieved by merging VNFs. However, the energy waste and device wear for large-scale collections of servers (e.g., cloud networks and data centers) caused by sporadic request updating are ignored. To solve these problems, we propose an energy-aware routing and adaptive delayed shutdown (EAR-ADS) algorithm for dynamic SFC deployment, which includes the following features: 1) energy-aware routing (EAR): by considering a practical deployment environment, a flexible solution is developed based on reusing open servers and selecting paths with the aims of balancing energy and resources and minimizing the total cost and 2) adaptive delayed shutdown (ADS): the delayed shutdown time of the servers can be flexibly adjusted in accordance with the usage of each device in each time slot, thus eliminating the no-load wait time of the servers and frequent on/off switching. Therefore, the EAR-ADS can achieve dual-energy savings by both decreasing the number of open servers and reducing the idle/switching energy consumption of these servers. The simulation results show that EAR-ADS not only minimizes the cost of energy and resources but also achieves an excellent success rate and stability. Moreover, EAR-ADS is efficient compared with an improved Markov algorithm (SAMA), reducing the average deployment time by more than a factor of 40.

关键词： Servers Energy consumption Internet of Things Hardware network function virtualization Routing Heuristic algorithms Dynamic deployment energy efficient network function virtualization (NFV) service function chain (SFC)

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Low-Latency and Resource-Efficient Service function Chaining Orchestration in network function virtualization

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IEEE INTERNET OF THINGS JOURNAL 2020年第7期7卷 5760-5772页

作者： Sun, Gang Xu, Zhu Yu, Hongfang Chen, Xi Chang, Victor Vasilakos, Athanasios V. Univ Elect Sci & Technol China Minist Educ Key Lab Opt Fiber Sensing & Commun Chengdu 611731 Peoples R China Southwest Minzu Univ Sch Comp Sci & Technol Chengdu 610041 Peoples R China Teesside Univ Sch Comp & Digital Technol Middlesbrough TS1 3BX Cleveland England Lulea Univ Technol Dept Comp Sci Elect & Space Engn S-14671 Lulea Sweden Fuzhou Univ Dept Comp Sci & Technol Fuzhou Peoples R China

Recently, network function virtualization (NFV) has been proposed to solve the dilemma faced by traditional networks and to improve network performance through hardware and software decoupling. The deployment of the service function chain (SFC) is a key technology that affects the performance of virtual network function (VNF). The key issue in the deployment of SFCs is proposing effective algorithms to achieve efficient use of resources. In this article, we propose an SFC deployment optimization (SFCDO) algorithm based on a breadth-first search (BFS). The algorithm first uses a BFS-based algorithm to find the shortest path between the source node and the destination node. Then, based on the shortest path, the path with the fewest hops is preferentially chosen to implement the SFC deployment. Finally, we compare the performances with the greedy and simulated annealing (G-SA) algorithm. The experiment results show that the proposed algorithm is optimized in terms of end-to-end delay and bandwidth resource consumption. In addition, we also consider the load rate of the nodes to achieve network load balancing.

关键词： Delays Heuristic algorithms Load management Approximation algorithms Optimization network function virtualization Hardware End-to-end delay network function virtualization (NFV) resource consumption service function chain (SFC)

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State of the Art and Research Challenges in the Security Technologies of network function virtualization

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IEEE INTERNET COMPUTING 2020年第1期24卷 25-35页

作者： Wu, Xiaochun Hou, Kaiyu Leng, Xue Li, Xing Yu, Yinbo Wu, Bo Chen, Yan Zhejiang Gongshang Univ Hangzhou Peoples R China Northwestern Univ Evanston IL USA Northwestern Univ Dept Elect Engn & Comp Sci Evanston IL USA Zhejiang Univ Comp Sci & Technol Hangzhou Peoples R China Zhejiang Univ Coll Comp Sci & Technol Hangzhou Peoples R China Wuhan Univ Sch Elect Informat Wuhan Peoples R China Tsinghua Univ Beijing Peoples R China

In recent years, network function virtualization (NFV) has drawn considerable attention due to its potential for service agility and low total cost of ownership. As the core of an NFV implementation, security issues in the management and control platform must be comprehensively addressed-from architectural concept to deployment. In this article, we first analyze the state of the security architecture based on ETSI-NFV, and then propose useful security practices for an NFV-based management and control ecosystem. To encourage future research, we also identify the ongoing research challenges and open security issues relevant to the NFV.

关键词： Computer security Computer architecture Monitoring network function virtualization Hardware Ecosystems network function virtualization Service chain Microservice Virtualized network function

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Efficient algorithms to minimize the end-to-end latency of edge network function virtualization

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2020年第10期11卷 3963-3974页

作者： Ghai, Karanbir Singh Choudhury, Salimur Yassine, Abdulsalam Lakehead Univ Dept Comp Sci Thunder Bay ON Canada Lakehead Univ Dept Software Engn Thunder Bay ON Canada

In future wireless networks, network function virtualization will lay the foundation for establishing a new dynamic resource management framework to efficiently utilize network resources. The main problem discussed in this paper is the minimization of total latency for an edge network and how to solve it efficiently. A model of users, virtual network functions and hosting devices has been taken, and is used to find the minimum latency using integer linear programming. The problem is NP-hard and takes exponential time to return the optimal solution. We apply the stable matching based algorithm to solve the problem in polynomial time and then utilize local search to improve its efficiency further. From extensive performance evaluation, it is found that our proposed algorithm is very close to the optimal scheme in terms of latency and better in terms of time complexity.

关键词： network function virtualization Hosting device Latency Stable matching Local search

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CoNFV: A Heterogeneous Platform for Scalable network function virtualization

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ACM TRANSACTIONS ON RECONFIGURABLE TECHNOLOGY AND SYSTEMS 2020年第1期14卷 1-29页

作者： Zhang, Xuzhi Shao, Xiaozhe Provelengios, George Dumpala, Naveen Kumar Gao, Lixin Tessier, Russell Univ Massachusetts Dept Elect & Comp Engn Amherst MA 01003 USA

network function virtualization (NFV) is a powerful networking approach that leverages computing resources to perform a time-varying set of network processing functions. Although microprocessors can be used for this purpose, their performance limitations and lack of specialization present implementation challenges. In this article, we describe a new heterogeneous hardware-software NFV platform called CoNFV that provides scalability and programmability while supporting significant hardware-level parallelism and reconfiguration. Our computing platform takes advantage of both field-programmable gate arrays (FPGAs) and microprocessors to implement numerous virtual network functions (VNF) that can be dynamically customized to specific network flow needs. The most distinctive feature of our system is the use of global network state to coordinate NFV operations. Traffic management and hardware reconfiguration functions are performed by a global coordinator that allows for the rapid sharing of network function states and continuous evaluation of network function needs. With the help of state sharing mechanism offered by the coordinator, customer-defined VNF instances can be easily migrated between heterogeneous middleboxes as the network environment changes. A resource allocation and scheduling algorithm dynamically assesses resource deployments as network flows and conditions are updated. We show that our deployment algorithm can successfully reallocate FPGA and microprocessor resources in a fraction of a second in response to changes in network flow capacity and network security threats including intrusion.

关键词： network function virtualization coordinator heterogeneous middle-boxes FPGA performance-aware VNF deployment

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Traffic routing in stochastic network function virtualization networks

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JOURNAL OF network AND COMPUTER APPLICATIONS 2020年 169卷 102765-102765页

作者： Yang, Song Li, Fan Trajanovski, Stojan Fu, Xiaoming Beijing Inst Technol Sch Comp Sci & Technol Beijing Peoples R China Microsoft London England Univ Gottingen Inst Comp Sci Gottingen Germany

network function virtualization (NFV) is emerging as an attractive solution, which can transform complex network functions from the dedicated hardware implementations into software instances running in a virtualized environment In NFV, the requested service is implemented by a sequence of Virtual network functions (VNF) that can run on generic servers by leveraging the virtualization technology. These VNFs are placed in a predefined order, which is also known as the Service function Chaining (SFC). While most of the existing work on traffic routing in NFV networks assume deterministic link delay and bandwidth, the real-life network usually behaves in a stochastic manner, due to e.g., inaccurate data, expired exchanged information, insufficient estimation to the network. Motivated by this, we consider the stochastic NFV networks, where the link bandwidth and delay are assumed to be random variables and their cumulative distribution functions are known. We first study how to calculate the delay and bandwidth value in an SFC such that their realizing probabilities are satisfied. Subsequently, we formally define the traffic routing problem in stochastic NFV networks and prove it is NP-hard. We present an exact solution and a tunable heuristic to solve this problem. The proposed heuristic is a sampling-based algorithm, and it leverages the Tunable Accuracy Multiple Constraints Routing Algorithm (TAMCRA) to find a multi-constraint path for each adjacent VNF pair. It dynamically adjusts the link weights as well as delay and bandwidth realizing probability constraint after finding the path for each VNF pair so that the cumulated probabilities will not violate the specified values. Finally, we evaluate the performance of the proposed algorithms via extensive simulations.

关键词： network function virtualization Routing Stochastic Delay Bandwidth

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Joint optimization of function mapping and preemptive scheduling for service chains in network function virtualization

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2020年 108卷 1112-1118页

作者： Yao, Hong Xiong, Muzhou Li, Hui Gu, Lin Zeng, Deze China Univ Geosci Sch Comp Sci Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan Peoples R China

The idea of network function virtualization (NFV) is to decouple of network functions from dedicated hardwares to obtain higher flexibility in terms of network management and maintenance. Although the problem of function placement and scheduling in NFV has drawn much attention in recent years, existing studies only consider the precedence constraints between network functions within a service but lacking for the interactions among services. In this paper, under the premise of satisfying the precedence conditions of forming the service chain, we study how to minimize the completion time of the whole system through efficient mapping and preemptive scheduling of functions for multiple service chains. We firstly model this issue as an Integer Linear Programming (ILP) problem. To avoid the computational complexity of ILP, an online preemptive algorithm is designed. Extensive simulations are conducted to validate the effectiveness of the proposed algorithm. The simulation results indicate that our algorithm is suitable for placement and scheduling of functions for multiple service chains in NFV. (C) 2018 Elsevier B.V. All rights reserved.

关键词： network function virtualization function mapping Preemptive scheduling Service chain

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A network function virtualization System for Detecting Malware in Large IoT Based networks

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2020年第6期38卷 1218-1228页

作者： Guizani, Nadra Ghafoor, Arif Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

The exponential growth in the use of Internet of Things (IoT) devices has introduced numerous challenges, in particular dealing with new security threats. In addition, for connecting heterogeneous devices using different protocols, large networks need resilient software-based security systems that can defend against unprecedented attacks for which the traditional security countermeasures prove to be ineffective. Furthermore, to deal with the ever growing onslaught on data and networks, modern security systems need to utilize novel machine learning mechanisms. This paper proposes a software-based architecture that provides network function virtualization (NFV) capability to combat malware spread for heterogeneous IoT networks. To build a scalable and generalized Intrusion Detection System (IDS), we propose for these networks a RNN-LSTM learning model that can predict malware attacks in a timely manner for the NFV to deploy appropriate countermeasures. In addition, we investigate the scalability of the network and discuss how the generalized IDS can deal with a broad range of malwares that can be detected. The analysis utilizes the susceptible (S), exposed (E), infected (I), and resistant (R) (SEIR) epidemic model to moniter the spread of the malware attack and subsequently provides patching to the system. Our analysis focuses primarily on the feasibility and the performance evaluation of the proposed integrated RNN-LSTM and NFV architecture.

关键词： Malware Protocols Security Machine learning Neural networks network function virtualization Internet of Things network function virtualization recurrent neural network software based architecture IoT devices

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Resources Allocation at the Physical Layer for network function virtualization Deployment

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2020年第3期69卷 2771-2784页

作者： Xie, Ning Luo, Jianping Shenzhen Univ Coll Elect & Informat Engn Guangdong Key Lab Intelligent Informat Proc Shenzhen 518060 Peoples R China Shenzhen Univ Coll Elect & Informat Engn Shenzhen Key Lab Media Secur Shenzhen 518060 Peoples R China

Resource Allocation (RA) is one of the important factors in network function virtualization (NFV) deployment. As physical (PHY) layer resources are limited, e.g., transmitted energy and channel uses, the RA problem at the PHY layer for NFV deployment has become a fast-growing problem, especially for supporting ultra-reliable and low-latency communications (URLLC). Moreover, different nodes in NFV have different requirements for end-to-end communication, e.g., a controller has more stringent reliability requirements than does a logical node. There is a need for efficient and robust RA algorithms at the PHY layer for NFV deployment. To illustrate these challenges, we consider an up-link (UL) transmission protocol for NFV deployment, in which wireless transmissions with short packets are considered, and both the packet length and the transmission power are adjustable. Then, for three NFV deployment scenarios, we formulate three RA problems as three optimization problems to obtain the optimal parameters. Since these optimization problems are highly non-convex and they include excessive constraint conditions, the global optimal solutions are hard to obtain and are even infeasible for the conventional heuristic algorithms due to their low convergence efficiency. To address these problems, in this paper, the intelligent scheme of the modified shuffled frog-leaping algorithm (MSFLA) based on improved extremal optimization (EO) is applied to design RA algorithms. Three RA algorithms are designed for three NFV deployment scenarios to evaluate the quality of the solutions produced by the MSFLA-EO scheme. We perform simulations of three proposed RA algorithms in terms of various performance parameters. The experimental results are encouraging and demonstrate the efficiency of the proposed RA algorithms.

关键词： network function virtualization resource allocation physical layer URLLC shuffled frog-leaping algorithm

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