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FullSight: A Feasible Intelligent and Collaborative Framework for Service function Chains Failure Detection

IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2022年第4期19卷 4546-4565页

作者： Guo, Kuo Chen, Jia Dong, Ping Liu, Shang Gao, Deyun Beijing Jiaotong Univ Natl Engn Res Ctr Adv Network Technol Dept Elect & Informat Engn Beijing 100044 Peoples R China

network function virtualization (NFV) is a ground-breaking technology that decouples network functions (NFs) from customized hardware to support more flexible network services and network resource allocation. However, these improvements also lead to an increase in the possibility of service function chain (SFC) failure due to hardware failures, software bugs, or resource contention. This could lead to minor problems or even serious consequences. Unfortunately, the existing failure detection methods have multiple issues, such as small detection range, single detection function, heavy overhead, and low accuracy. Consequently, we propose FullSight, a feasible framework based on deep learning (DL) models that can efficiently integrate both the control plane and programmable data plane for fault detection and classification. This framework obtains the status and indicators of components and network that cause service quality performance degradation through two planes. These indicators are ultimately sent to the knowledge plane for preprocessing, dimensionality reduction, and fault analysis. In addition, we propose two algorithms based on text convolutional neural network (textCNN) and bidirectional encoder representations from transformers (BERT) to classify SFC faults. We implement and evaluate the proposed FullSight prototype extensively on a prototype with thirteen programmable switches and twenty end-hosts. Our experimental results show that FullSight can rapidly and accurately detect and identify eight categories of fine-grained SFC failures, compared with other state-of-the-art methods. Besides, compared with SFC Path Tracer and Pingmesh, our framework can reduce the average bandwidth overhead of the data plane by 57% and 84%, respectively, and achieve detection accuracy of more than 98%.

关键词： Fault detection Probes Classification algorithms Prototypes virtualization Service function chaining Monitoring network function virtualization service function chain collaborated detection programmable data plane deep learning

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Demo: Towards Rapid Prototyping network-Slicing Solutions in Software-Defined networks

Demo: Towards Rapid Prototyping Network-Slicing Solutions in...

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IEEE/IFIP network Operations and Management Symposium (NOMS)

作者： Windisch, Fritz Abedi, Kamyar Nguyen, Giang T. Strufe, Thorsten KIT Chair Privacy & Secur Kastel Karlsruhe Germany Tech Univ Dresden Hapt Commun Syst Dresden Germany Ctr Tactile Internet Human in the Loop CeTI Dresden Germany

ISBN: (纸本)9798350327939;9798350327946

As part of the most recent mobile broadband standards, 5G and 6G, network slicing solutions will shape the future of networks. By employing network slicing, network operators can protect participants against different attacks over the network by isolating devices and providing resource guarantees. Currently, to evaluate new network-slicing solutions, network researchers or engineers have to either evaluate the solution in a virtual environment that can not accurately scale to the performance of hardware platforms or invest significant portions of time in network configuration on hardware platforms. To quickly prototype network slicing solutions and other solutions depending on software-defined networking (SDN) features, we introduce a hardware abstraction layer featuring a vendor-independent API to manage hardware platforms and a new testbed solution featuring topologies similar to common network evaluation platforms like mininet. In this demo, we showcase a network-slicing solution leveraging SDN. The audience can visually observe the performance of the communication channel before and after denial-of-service attacks and with and without the secure network slicing.

关键词： network slicing Prototypes network function virtualization Software-defined networking

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Non-invasive performance prediction of high-speed softwarized network services with limited knowledge

Non-invasive performance prediction of high-speed softwarize...

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IEEE Conference on Computer Communications (IEEE INFOCOM)

作者： Liu, Qiong Zhang, Tianzhu Linguaglossa, Leonardo Telecom Paris Inst Polytech Paris LTCI F-91120 Palaiseau France Nokia Bell Labs F-91300 Massy France

ISBN: (纸本)9798350383515;9798350383508

Modern telco networks have experienced a significant paradigm shift in the past decade, thanks to the proliferation of network softwarization. Despite the benefits of softwarized networks, the constituent software data planes cannot always guarantee predictable performance due to resource contentions in the underlying shared infrastructure. Performance predictions are thus paramount for network operators to fulfill Service-Level Agreements (SLAs), especially in high-speed regimes (e.g., Gigabit or Terabit Ethernet). Existing solutions heavily rely on in-band feature collection, which imposes non-trivial engineering and data-path overhead. This paper proposes a non-invasive performance prediction approach, which complements state-of-the-art solutions by measuring and analyzing low-level features ubiquitously available in the network infrastructure. Accessing these features does not hamper the packet data path. Our approach does not rely on prior knowledge of the input traffic, VNFs' internals, and system details. We show that (i) low-level hardware features exposed by the NFV infrastructure can be collected and interpreted for performance issues, (ii) predictive models can be derived with classical ML algorithms, (iii) and can be used to predict performance impairments in real NFV systems accurately. Our code and datasets are publicly available (1).

关键词： network function virtualization performance prediction service function chaining

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Investigation of Container network function Deployment Costs in the Edge Cloud 27

Investigation of Container Network Function Deployment Costs...

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27th Conference on Innovation in Clouds, Internet and networks (ICIN)

作者： Kien Nguyen Simonovski, Filip Loh, Frank Hossfeld, Tobias Nguyen Huu Thanh Univ Wurzburg Inst Comp Sci Wurzburg Germany Hanoi Univ Sci & Technol Hanoi Vietnam Univ Augsburg Augsburg Germany

ISBN: (纸本)9798350393767;9798350393774

Service function Chains (SFCs) can be used with containerization to efficiently enable the ever-increasing Internet of Things (IoT) deployments in heterogeneous edge-cloud environments. In this context, SFC schedulers often employ mechanisms such as migration and consolidation of Containerized network functions (CNF) to adapt to dynamic environments. However, the costs of the CNF lifecycle are often not investigated, especially deep into its states and state transitions, have created a gap between theoretical research and practical implementation. To this end, this paper comprehensively examines the capability of the edge-cloud in accommodating CNF-based IoT deployments with a key focus on the CNF lifecycle invocation cost, including latency, resource, and energy consumption. Our findings show the actual cost of using and reconfiguring CNFs, which is a common SFC optimization technique. We then provide a comprehensive profiling that could be used to develop realistic SFC placement strategies and algorithms.

关键词： Cloud Computing network function virtualization Internet of Things Service Migration

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A Service Migration Strategy for Resilient Multi-Domain networks in Outage Scenarios 8

A Service Migration Strategy for Resilient Multi-Domain Netw...

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IEEE 8th International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)

作者： Giarre, Federico Hadjadj-Aoul, Yassine Ait-Chellouche, Soraya Univ Rennes INRIA CNRS IRISA Rennes France

ISBN: (纸本)9798350319514

network slicing has emerged as a crucial technology in 5G and post-5G networks, enabling the creation of customized logical networks on a shared physical infrastructure. However, the problem of service placement, which entails determining the optimal deployment of network functions within each slice, becomes particularly challenging during outage scenarios. Service migration serves as a critical technique for reconfiguring and relocating network functions, thereby ensuring the resilience and availability of the slices. This paper presents a service migration strategy specifically designed for resilientmulti-orchestrator multi-domain networks. Our approach considers multi-domain services composed of components deployed across different network domains using Kubernetes clusters. The abstract nature of this migration strategy allows for its adaptation to different orchestrators within a cluster, facilitating the integration of more diverse and heterogeneous systems.

关键词： network function virtualization Resiliency Service Migration

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Baseband-function Placement With Multi-Task Traffic Prediction for 5G Radio Access networks

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2022年第4期19卷 5104-5119页

作者： Zorello, Ligia Maria Moreira Bliek, Laurens Troia, Sebastian Guns, Tias Verwer, Sicco Maier, Guido Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy Meta Inc London England TU Eindhoven Dept Ind Engn & Innovat Sci NL-5600 MB Eindhoven Netherlands Vrije Univ Brussel Econ & Social Sci & Solvay Business Sch B-1050 Brussels Belgium Delft Univ Technol Fac Elect Engn Math & Comp Sci NL-2628 CD Delft Netherlands

The 5G Radio Access network (RAN) virtualization aims to improve network quality and lower the operator's costs. One of its main features is the functional split, i.e., dividing the instantiation of RAN baseband functions into different units over metro-network nodes. However, its optimal placement is non-trivial: it depends on the application requirements and on the expected traffic volume, whose daily variation highly impacts the total power consumption. Current optimization solutions fail to provide a placement solution capable of handling traffic fluctuations. In fact, the standard machine learning algorithms used in the literature for planning the network resources in advance result in an allocation that is inadequate to carry the actual traffic at all the time-slots. Hence, we must reserve an artificial buffer capacity in the nodes to ensure feasibility. Instead, our proposed method exploits a fine-grained two-step multi-task algorithm that predicts the mean and quantile traffic, making the artificial capacity no longer necessary. The subsequent placement uses mixed-integer linear programming and a heuristic. The former considers the expected traffic in the objective function (to estimate costs) and the quantile in the constraints (to enforce capacity limits). The heuristic combines the mean and quantile results to minimize the power and comply with the requirements. While using sufficiently large artificial buffers guarantees robustness with a mild power increase compared to the oracle, the fine-grained multi-task model improves the results, reducing the power consumption compared to the mean and meets all constraints. The heuristic enables significant computational time reduction.

关键词： Baseband Optimization Power demand Prediction algorithms Multitasking Machine learning Costs 5G radio access network functional split network function virtualization traffic prediction mathematical optimization machine learning energy saving

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Fast recovery for online service function chaining interruption using adaptive migration

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CLUSTER COMPUTING-THE JOURNAL OF networkS SOFTWARE TOOLS AND APPLICATIONS 2022年第2期25卷 1321-1339页

作者： Xie, Jingzhao Zhou, Run Sun, Gang Sun, Jian Yu, Hongfang Univ Elect Sci & Technol China Minist Educ Key Lab Opt Fiber Sensing & Commun Chengdu Peoples R China Agile & Intelligent Comp Key Lab Sichuan Prov Chengdu Peoples R China Peng Cheng Lab Shenzhen Peoples R China

With the rapid development of wireless communication technology and the rapid popularization of various mobile devices, an increasing number of users want the ability to access their service requests conveniently anytime and anywhere. In order to avoid ongoing service interruption, the user's SFC should be quickly migrated to ensure the continuation of mobile communication and seamless connection of online services (i.e., no interruption of ongoing services) when the user moves out of the service area of the original access point. However, most of the current research on service function chaining (SFC) migration focuses on how to achieve migration and ignores the fact that a rapid recovery response to avoid the sudden interruption of online services is the fundamental purpose of migration in this situation. This paper shows that implementing fast remapping on the mobile SFC is an assurance of its service continuity. And we propose a migration-aware and quick reresponse algorithm to realize the rapid migration and reresponse of mobile service requests. Furthermore, to ensure both the success rate and rationality of service migration, the algorithm also considers the operation cost and resource consumption of migration. The simulation results show that the algorithm effectively optimizes the migration time, and meanwhile it can choose the migration scheme with the highest matching degree for SFC based on the current network state efficiently and flexibly.

关键词： network function virtualization Service function chain Migration policy Adaptive migration Online migration Quality of service Survivability

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Cost-Aware Topological Decomposition of Virtual network function Forwarding Graphs

Cost-Aware Topological Decomposition of Virtual Network Func...

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IEEE Conference on Global Communications (IEEE GLOBECOM) - Intelligent Communications for Shared Prosperity

作者： Azhdari, Azadeh Ebrahimzadeh, Amin Afrasiabi, Seyedeh Negar Szabo, Robert Mouradian, Carla Li, Wubin Glitho, Roch. H. Concordia Univ CIISE Montreal PQ Canada Ericsson Res Montreal PQ Canada Ericsson Res Budapest Hungary Univ Western Cape Comp Sci Programme Cape Town South Africa

ISBN: (纸本)9798350310900

To realize a network Service (NS) in a network function virtualization (NFV) network, it is needed to form an ordered set of connected Virtual network functions (VNFs), commonly referred to as VNF Forwarding Graph (VNF-FG), and then embed it onto the substrate network. Forming a VNF-FG is a challenging step of NFV resource allocation (NFV-RA), especially when the VNFs can be further decomposed into different sub-functions. In this paper, we propose a cost-aware algorithm to solve the problem of topological decomposition of VNF-FGs with the main objective of minimizing the embedding cost while satisfying the given service requirements. The simulation results indicate that our proposed algorithm outperforms the existing benchmark in terms of embedding cost, while being significantly scalable compared to the brute-force approach.

关键词： network function virtualization Virtual network function VNF Decomposition Embedding Cost

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Cost-Efficient Virtual network function Placement in an Industrial Edge System: A Proposed Method

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IEEE SYSTEMS MAN AND CYBERNETICS MAGAZINE 2023年第1期9卷 10-17页

作者： Liu, Mingyue Alias, Syazwina Binti SEGi Univ Dept Informat Technol Petaling Jaya 47810 Malaysia

Edge computing has been a promising framework to provide effective computing services for edge users in most industrial environments. Due to the limited resources at the edge, it is not suitable for massive requirements such as the virtual reality process, communication, and so on. Cloud computing can provide sufficient resources for those requirements, but it has some latency lags. Industrial edge clouds enable flexible service providers for industrial applications by merging edge and cloud computing. The virtual network function (VNF) is one approach, while placement is a dominant solution. However, this solution may increase the cost of communication as the nodes are more distant. In this article, we investigate the resource allocation problem for VNF placement in industrial edge systems. The aim is to minimize the overall cost of the whole placement procedure, including operating cost, communication cost, and placement cost. We formulate this VNF placement problem as an integer programming problem, and due to the complexity of the problem, we propose a heuristic method to solve it. Numerical simulation shows that our proposed method can significantly cut down the cost while meeting the multiple resource constraints.

关键词： Integer programming Cloud computing Costs Edge computing Virtual reality Numerical simulation Real-time systems network function virtualization Fourth Industrial Revolution

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Optimal Flow Collector Placement In Experimental networks 9

Optimal Flow Collector Placement In Experimental Networks

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9th IEEE European Symposium on Security and Privacy (EuroS and P)

作者： Sankaran, Ganesh Chennimalai Raghothaman, Mukund Collins, M. Patrick USC ISI Los Angeles CA 90089 USA USC Los Angeles CA USA

ISBN: (纸本)9798350367324;9798350367294

For operational security personnel, network based data collection requires balancing the need for complete collection against the risks of drowning in redundant data. We have developed a formulation of this problem of redundant collection which converts the problem into a maxflow problem, enabling us to determine optimal sensor placement assuming complete collection. We discuss the formulation and how it can accommodate multiple security requirements and demonstrate its implementation on multiple candidate networks.

关键词： network forensics network function virtualization network monitoring optimization security security experimentation testbeds

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