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

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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When Cloud Media Meets network function virtualization: Challenges and Applications

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IEEE MULTIMEDIA 2017年第3期24卷 72-82页

作者： Jin, Yichao Wen, Yonggang Nanyang Technol Univ Singapore Singapore Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore

network function virtualization (NFV)could transform cloud network architecture by reducing the cost of operating media services. As this survey shows, the proposed NFV-enabled media cloud system is both flexible and ... 详细信息

关键词： Cloud Computing network function virtualization virtualization Mobile Communication Resource Management network function virtualization Multimedia networking Cloud virtualization network function virtualization NFV Mobile

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Energy efficiency with service availability guarantee for network function virtualization

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2021年 119卷 140-153页

作者： Mai, Liuyang Ding, Yi Zhang, Xiaoning Fan, Lang Yu, Shui Xu, Zhichao Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Peoples R China Univ Technol Sydney Sch Software Sydney NSW Australia

Following the trend of network function virtualization (NFV), dedicated hardware middleboxes are replaced with innovative and flexible software middleboxes also known as Virtual network functions (VNFs). An ordered sequence of VNFs composing a logical service is called Service function Chain (SFC). VNFs are generally run on commodity servers. In this way, the capital and operational expenditures of buying and maintaining dedicated hardware for telecom operators can be greatly reduced. One of the key issues in NFV is the optimal VNF placement and service chaining to achieve energy efficiency. However, the current NFV energy saving approaches seem to consider energy minimization as the only objective to be optimized. Little or no attention is given to other important aspects, e.g., service availability, which is paramountly important to fulfill Service Level Agreement (SLA) for telecom operators. This paper investigates the energy efficiency optimization with service availability guarantee in NFV-enabled networks. We firstly propose a novel green orchestration NFV architecture. Then, an energy-efficient VNF placement framework guaranteeing service availability is presented under the proposed architecture, and evaluated by extensive simulations. Open research issues and technical challenges in this emerging area are also presented. (C) 2021 Elsevier B.V. All rights reserved.

关键词： network function virtualization Service function chain Reliability Protection Lagrangian relaxation

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Optimizing the Cloud Resources, Bandwidth and Deployment Costs in Multi-Providers network function virtualization Environment

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IEEE ACCESS 2019年 7卷 46898-46916页

作者： Eramo, Vincenzo Lavacca, Francesco Giacinto Sapienza Univ Rome DIET I-00184 Rome Italy Fdn Ugo Bordoni I-00161 Rome Italy

The introduction of network function virtualization (NFV) leads to a new business model in which the Telecommunication Service Provider needs to rent cloud resources to infrastructure provider (InP) at prices as low as possible. Lowest prices can be achieved if the cloud resources can be rented in advance by allocating long-term virtual machines (VM). This is in contrast with the short-term VMs that are rented on demand and have higher costs. For this reason, we propose a proactive solution in which the cloud resource rent is planned in advance based on peak traffic knowledge. We illustrate the problem of determining the cloud resources in cloud infrastructures managed by different InPs and so as to minimize the sum of cloud resource, bandwidth and deployment costs. We formulate an integer linear problem (ILP) and due to its complexity, we introduce an efficient heuristic approach allowing for a remarkable computational complexity reduction. We compare our solution to a reactive solution in which the cloud resources are rented on demand and dimensioned according to the current traffic. Though the proposed proactive solution needs more cloud and bandwidth resources due to its peak allocation, its total resources cost may be lower than the one achieved when a reactive solution is applied. That is a consequence of the higher cost of short-term VMs. For instance, when a reactive solution is applied with traffic variation times of ten minutes, our proactive solution allows for lower total costs when the long-term VM rent is lower than the short-term VM one by 33%.

关键词： network function virtualization cloud infrastructure short-term virtual machine Viterbi algorithm

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Blockchain-Enabled SLA Compliance for Crowdsourced Edge-Based network function virtualization

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IEEE network 2021年第5期35卷 58-65页

作者： Rahman, Mohammad Saidur Khalil, Ibrahim Atiquzzaman, Mohammed RMIT Univ Sch Comp Technol Melbourne Vic Australia Univ Oklahoma Sch Comp Sci Norman OK 73019 USA

network function virtualization (NFV) allows edge devices to host different types of virtual network functions (VNFs) and support Computing in the network. Therefore, an edge device can abstract multiple VNFs of different infrastructure providers (InPs) as services and serve them at different times to act as a tenant for different InPs. Deploying edge devices is expensive and difficult to manage. Hence, crowdsourced edge devices can be used. To ensure the quality and availability of the services and the privacy of sensitive data of the service stakeholders, it is extremely important to establish a service level agreement (SLA) between an edge device owner and an InP. For monitoring of SLA compliance and enforcing accountability, a trusted platform is required. The traditional NFV management authority cannot be trusted due to its centralized characteristics. In this article, we propose a blockchain-powered framework for the SLA compliance of edge devices offering VNFs as services and introduce a smart contract-driven framework to establish trust in edge-based NFV. We analyze the performance of the proposed framework in the context of a private blockchain network.

关键词： Scalability Smart contracts Consensus algorithm Blockchains network function virtualization Stakeholders III-V semiconductor materials Edge computing Cloud computing

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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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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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Software-Defined network function virtualization: A Survey

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IEEE ACCESS 2015年 3卷 2542-2553页

作者： Li, Yong Chen, Min Tsinghua Univ Dept Elect Engn State Key Lab Microwave & Digital Commun Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China

Diverse proprietary network appliances increase both the capital and operational expense of service providers, meanwhile causing problems of network ossification. network function virtualization (NFV) is proposed to address these issues by implementing network functions as pure software on commodity and general hardware. NFV allows flexible provisioning, deployment, and centralized management of virtual network functions. Integrated with SDN, the software-defined NFV architecture further offers agile traffic steering and joint optimization of network functions and resources. This architecture benefits a wide range of applications (e.g., service chaining) and is becoming the dominant form of NFV. In this survey, we present a thorough investigation of the development of NFV under the software-defined NFV architecture, with an emphasis on service chaining as its application. We first introduce the software-defined NFV architecture as the state of the art of NFV and present relationships between NFV and SDN. Then, we provide a historic view of the involvement from middlebox to NFV. Finally, we introduce significant challenges and relevant solutions of NFV, and discuss its future research directions by different application domains.

关键词： Software-defined networks network function virtualization middlebox service chain network virtualization

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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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Service Deployment With Priority Queueing for Traffic Processing and Transmission in network function virtualization

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2023年第4期20卷 4861-4874页

作者： He, Fujun Oki, Eiji Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan Huawei Technol Co Ltd Shenzhen 518063 Peoples R China

network function virtualization enables service providers to flexibly deploy network services. The existing works mainly focus on function placement and capacity allocation without exploring traffic scheduling for service deployment, by adopting a first-in-first-out policy. It introduces inefficiency considering that different services vary in the delay requirements. This paper proposes a service deployment model with priority queuing for both traffic processing and transmission to minimize the deployment cost with satisfying the service delay constraints. We analyze the problem including proving its NP-hardness and the convexity of a subproblem. Based on the analysis, we develop a reinforcement learning-based approach to address the problem in a decomposition manner with a polynomial-time complexity in each episode. Several specific designs are introduced to fit the learning-based approach to the considered deployment problem with priority queueing. The numerical results show that the introduced approach achieves an objective value comparable to the optimal one obtained by brute force search with a computation time 10(3) times shorter. Compared to a conventional model with the first-in-first-out policy, the proposed model reduces the deployment cost by adopting a more flexible queueing policy.

关键词： network function virtualization service deployment priority queueing reinforcement learning

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