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5th International Conference on Computer Science and Software Engineering, CSSE 2022

作者： Qiu, Rixuan Qin, Yongtai Li, Yuancheng Zhou, Xin Fu, Junfeng Li, Wei Yan, Juan Shi, Jie State Grid Jiangxi Information & Telecommunication Company China School of Control and Computer Engineering North China Electric Power University China State Grid Jiangxi Electric Power Company Yingtan Power Supply Branch China Co. Ltd. China

ISBN: (纸本)9781450397780

In recent years, with the increase in the variety of communication devices, as well as the rapid development of the Internet of Things, edge computing, and machine learning, the existing security solutions can neither solve the problem of increasing fragmentation of security needs and security scenarios, nor the problem of the mismatch between security protection means and business scenarios, so the new software-defined security middle platform architecture is proposed. The infrastructure plane is connected to the architecture through network function virtualization. The security middle platform has the advantages of both the data middle platform and the business middle platform is designed to solve the fragmentation problem. Hybrid cloud environment is designed according to the cost, expansion, and security requirements. The Control plane solves the matching problem for the middle platform resource pool through flexible and intelligent scheduling. The small forward platform design of the application plane further reduces the development cost. © 2022 ACM.

关键词： network function virtualization

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Resource-Aware Reliability Assurance of Service function Chain 11th

Resource-Aware Reliability Assurance of Service Function Cha...

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11th International Conference on Computer Engineering and networks, CENet2021

作者： Zhang, Shaojun Ji, Yutong Cheng, Yufan Wang, Ying Yu, Peng State Grid Jibei Information and Telecommunication Company Beijing China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9789811665530

Although new technologies as network function virtualization (NFV) and Service function Chain (SFC) technology improve the deployment efficiency of network functions and the speed of service delivery, the reliability of the nodes in the service function chain will be reduced. With the increase of the length of the service function chain, the overall reliability will be greatly reduced. In order to improve the reliability of service function chain and reduce resource consumption, this paper realizes the reliability guarantee of resource-aware service function chain. Firstly, the reliability calculation model is realized based on the neural network, and the model is trained with the randomly generated service function chain data. The reliability of the model is verified by comparing the calculated data with the approximate calculated data. Then greedy shared backup is adopted to guarantee the service function chain and the node with the optimal improvement rate is selected as the newly added backup node. The simulation results verify that the proposed algorithm can effectively reduce the consumption of backup resources and improve resource utilization. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： network function virtualization

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Deployment strategy of resource optimized service function chain in NFV environment

Deployment strategy of resource optimized service function c...

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2022 International Conference on Cryptography, network Security, and Communication Technology, CNSCT 2022

作者： Chen, Xiaoxiao Shi, Jiugen He, Yong Li, Wenhao School of Computer and Information Hefei University of Technology Hefei China

ISBN: (数字)9781510654822

ISBN: (纸本)9781510654815

With the development of the new generation mobile communication technology, the application of network function virtualization (NFV) technology has become a boom. With NFV, virtual network functions (VNFs) are deployed in the form of service function chain (SFC), so how to place VNFs in the best position has become a challenge. This paper studies this challenge to maximize resource utilization and minimize energy cost. Specifically, a two-stage deployment strategy (TSBA) is designed. Firstly, a matching algorithm (MA) based on weighted graph matching is proposed to improve resource utilization. Then the idle server is shut down by VNF migration method to reduce the cost of server energy consumption. The experimental results show that the two-stage deployment strategy proposed in this paper effectively improves the resource utilization and reduces the energy consumption compared with the existing methods. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： network function virtualization

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MTDNS: Moving Target Defense for Resilient DNS Infrastructure

MTDNS: Moving Target Defense for Resilient DNS Infrastructur...

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Consumer Communications and networking Conference, CCNC IEEE

作者： Abdullah Aydeger Pei Zhou Sanzida Hoque Marco Carvalho Engin Zeydan Florida Institute of Technology Melbourne FL USA Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) Barcelona Spain

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

One of the most critical components of the Internet that an attacker could exploit is the DNS (Domain Name System) protocol and infrastructure. Researchers have been constantly developing methods to detect and defend against the attacks against DNS, specifically DNS flooding attacks. However, most solutions discard packets for defensive approaches, which can cause legitimate packets to be dropped, making them highly dependable on detection strategies. In this paper, we propose MTDNS, a resilient MTD-based approach that employs Moving Target Defense techniques through Software Defined networking (SDN) switches to redirect traffic to alternate DNS servers that are dynamically created and run under the network function virtualization (NFV) framework. The proposed approach is implemented in a testbed environment by running our DNS servers as separate Virtual network functions, NFV Manager, SDN switches, and an SDN Controller. The experimental result shows that the MTDNS approach achieves a much higher success rate in resolving DNS queries and significantly reduces average latency even if there is a DNS flooding attack.

关键词： Protocols Control systems network function virtualization Domain Name System Servers Floods Security Computer crime Software defined networking Resilience

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A Deep Neural network-Based Multi-Label Classifier for SLA Violation Prediction in a Latency Sensitive NFV Application

IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY

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IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY 2021年 2卷 2469-2493页

作者： Jalodia, Nikita Taneja, Mohit Davy, Alan Waterford Inst Technol Walton Inst Informat & Commun Syst Sci Emerging Networks Lab Res Div Waterford X91 WR86 Ireland CONNECT Ctr Future Networks & Commun Dublin Ireland Waterford Inst Technol Dept Comp & Math Waterford X91 WR86 Ireland Waterford Inst Technol Sch Business Dept Accountancy & Econ Waterford X91 WR86 Ireland

Recent advancements in the domain of network function virtualization (NFV), and rollout of next-generation networks have necessitated the requirement for the upkeep of latency-critical application architectures in future networks and communications. While Cloud service providers recognize the evolving mission-critical requirements in latency sensitive verticals such as autonomous driving, multimedia, gaming, telecommunications, and virtual reality, there is a wide gap to bridge the Quality of Service (QoS) constraints for the end-user experience. Most latency-critical services are over-provisioned on all fronts to offer reliability, which is inefficient towards scalability in the long run. To address this, we propose a strategy to model frequent violations on the application level as a multi-output target to enable more complex decision-making in the management of virtualised communication networks. In this work, we utilize data from a real-world deployment to configure and draft a realistic set of Service Level Objectives (SLOs) for a voice based NFV application, and develop a deep neural network based multi-label classification methodology to identify and predict multiple categories of SLO breaches associated with an application state. With this, we aim to gain granular SLA and SLO violation insights, enabling us to study and mitigate their impact and inform precision in drafting proactive scaling policies. We further compare the performance against a set of multi-label compatible machine learning classifiers, and address class imbalance in a multi-label setup. We perform a comprehensive evaluation to assess the performance on example-based, label-based and ranking-based measures, and demonstrate the suitability of deep learning in such a use-case.

关键词： Quality of service Predictive models Deep learning Service level agreements Measurement Machine learning Cloud computing network function virtualization machine learning deep learning neural networks classification algorithms multi-label classification prediction methods quality of service service level agreements quality of experience supervised learning artificial neural networks multi-layer neural network naive Bayes methods random forests decision trees boosting support vector machines imbalanced classification probabilistic classification

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SFC Based Cost-Aware Dynamic Multi-domain Service Deployment 18th

SFC Based Cost-Aware Dynamic Multi-domain Service Deployment

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18th Chinese Intelligent Systems Conference, CISC 2022

作者： Liu, Yanming Zhang, Chuangchuang Yang, Hongyong Zhang, Shuning Wang, Xingwei Li, Fuliang School of Information and Electrical Engineering Ludong University Yantai264025 China College of Computer Science and Engineering Northeastern University Shenyang110169 China

ISBN: (纸本)9789811962257

network function virtualization (NFV) achieves flexible service provisioning by Service function Chain (SFC). Nowadays, it is difficult to adapt to users’ dynamic service requests in multi-domain scenarios, since most existing proposals consider service deployment problems in static network scenarios. Therefore, in this paper, we study the cost-aware dynamic deployment of multi-domain services problem. First, we formulate the cost-aware dynamic multi-domain SFC deployment problem as a multi-objective optimization model with the target of service request acceptance ratio (SAR) maximization and service deployment cost (SDC) minimization. Then, by using Dijkstra algorithm, a greedy strategy based heuristic service deployment algorithm, called HSP, is presented to accommodate to more service requests and reduce service deployment cost. Finally, extensive simulations are conducted for performance evaluation, and simulation results demonstrate that HSP can obtain higher SAR and smaller SDC than comparison algorithms. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： network function virtualization

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Towards Service function Chaining and Embedding for Multi-Security Guarantee Levels 8

Towards Service Function Chaining and Embedding for Multi-Se...

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8th IEEE International Conference on Computer and Communications, ICCC 2022

作者： Wang, Ben Cao, Xiaojun Peng, Chengzong Li, Jun Zheng, Danyang School of Electronic and Information Engineering Soochow Univeristy China Georgia State University Department of Computer Science United States

ISBN: (纸本)9781665450515

In the emerging 5G networks, achieving security-aware data transmission needs to converting clients' requests into a service function chain (SFC), each service function (SF) of which provides a certain security guarantee level. As the virtualization technology is approaching to be mature, a service function may own multiple versions, whereas different versions provide various security guarantee levels with diverse costs. Thus, as more options are posted out by the multi-versions of SFs, establishing an SFC that meets the client's security guarantee level requirements becomes complex and challenging. In this paper, we study how to construct and embed a security-aware SFC onto a shared PN when multi-version SFs co-exist. We mathematically define this problem and name it security-aware service function chaining and embedding with multi-versions SFs (SFCE-MF). We prove this problem is NP-hard and proposes three critical heuristic algorithms to solve the problem, namely, security-first SF picking policy (SF -SP), cost-first SF picking policy (CF -SP) and security -cost balanced SF picking policy (SCB-SP). Our extensive simulations have shown that SCB-SP outperforms the other two regarding the variants of network size, the number of SF instances, and the security guarantee level requirements. © 2022 IEEE.

关键词： network function virtualization

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Designing a Reinforcement Learning Approach for the NFV Orchestration System with Energy Saving Optimization 8

Designing a Reinforcement Learning Approach for the NFV Orch...

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8th International Conference on Applied System Innovation, ICASI 2022

作者： Chen, Hung-Ming Chen, Shih-Ying Wang, Sheng-Kai Chen, Jian-Qun National Taichung University of Science and Technology No. 129 Section 3 Sanmin Rd North Dist. Taichung City Taiwan

ISBN: (纸本)9781665496506

With the development of 5G mobile system, the concept of network functions virtualization (NFV) is gaining importance. In the 3GPP standards organization's fifth generation mobile technology network specification, network slicing composed of virtualized network functions (VNFs) is proposed as one of the key technologies for 5G. In addition, for telecom operators, they are more concerned about how to deploy VNFs composed of network slices to optimize resource utilization and reduce resource wastage, in order to achieve operational cost savings. This study designs an energy-saving scheduler module for Kubernetes-based NFV orchestration system. And reinforcement learning approach is applied to make placement decisions for VNFs in network slices, scheduling to place the required VNFs in the least number of compute nodes without affecting deployed services. Further, the scheduler can leave idle compute nodes in shutdown or standby state to reduce resource usage and achieve energy efficiency. © 2022 IEEE.

关键词： network function virtualization

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SDN/NFV Enabled Security for an Enterprise network using Commodity Hardware 5

SDN/NFV Enabled Security for an Enterprise Network using Com...

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5th International Conference on Computing, Electronics and Communications Engineering. iCCECE 2022

作者： Saeed, Rizwan Qureshi, Safwan Farooq, Muhammad Umar Zeeshan, Muhammad National University of Sciences and Technology College of EME Islamabad Pakistan South East Technological University Emerging Networks Laboratory Walton Institute for Information and Communication Systems Science Waterford Ireland

ISBN: (数字)9781665489805

ISBN: (纸本)9781665489805

In this fast growing technology and tight integration of physical devices in conventional networks, the resource management and adaptive scalability is a problematic undertaking particularly when it comes to network security measures. Current work focuses on software defined network (SDN) and network function virtualization (NFV) based security solution to address problems in network and security management. However, deployment, configuration and implementation of SDN/NFV-based security solution remains a real challenge. To overcome this research challenge, this paper presents the implementation of SDN-NFVs based network security solution. The proposed methodology is based on using open network operating system (ONOS) SDN Controller with Zodiac FX Openflow switches and virtual network functions (VNF). VNF comprises of virtual security functions (VSF) which includes firewall, intrusion prevention system (IPS) and intrusion detection system (IDS). One of the main contributions of this research is the implementation of security solution of an enterprise, utilizing SDN-NFV platform and commodity hardware. We demonstrate the successful implementation, configuration and deployment of the proposed NFV-based network security solution for an enterprise. © 2022 IEEE.

关键词： network function virtualization

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A Mobility-Aware Service function Chain Migration Strategy Based on Deep Reinforcement Learning

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JOURNAL OF network AND SYSTEMS MANAGEMENT 2023年第1期31卷 21-21页

作者： Hu, Hefei Zhang, Wei Xu, Lingyi Qi, Panjie Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Sch Elect Engn Beijing 100876 Peoples R China

With the development of network function virtualization (NFV) and mobile edge computing (MEC), service function chaining (SFC) can be deployed more flexibly on the network edge to provide users with higher quality services. However, the mobility of users might affect the quality of the perceived service and even cause service unavailability. It is thus a challenge to better migrate the service function chains to reduce prevent such degradation and improve the migration success rate. This paper investigates the SFC migration timing decision problem in user predicted movement scenarios with a known mobile path and predicted arrival time. First, we establish an prediction model of user arrival time and formulate the SFC migration process as a mathematical model. Then, we model the SFC migration process as a Markov decision process, and propose a deep Q-network based SFC migration timing decision (DQN-MTD) algorithm. DQN-MTD can be useful to perceive and predict the state changes of network resources, and select appropriate migration timing for virtual network functions (VNFs) based on SFC migration information. The experimental results show that compared with existing algorithms, DQN-MTD algorithm can reduce the average service downtime by about 14%, improve the migration success rate of SFC by about 20%, and reduce the average VNF migration time and memory when network load is low.

关键词： network function virtualization User mobility Service function chain migration Deep reinforcement learning

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