@inproceedings{16219, abstract = {{Network function virtualization (NFV) proposes to replace physical middleboxes with more flexible virtual network functions (VNFs). To dynamically adjust to everchanging traffic demands, VNFs have to be instantiated and their allocated resources have to be adjusted on demand. Deciding the amount of allocated resources is non-trivial. Existing optimization approaches often assume fixed resource requirements for each VNF instance. However, this can easily lead to either waste of resources or bad service quality if too many or too few resources are allocated. To solve this problem, we train machine learning models on real VNF data, containing measurements of performance and resource requirements. For each VNF, the trained models can then accurately predict the required resources to handle a certain traffic load. We integrate these machine learning models into an algorithm for joint VNF scaling and placement and evaluate their impact on resulting VNF placements. Our evaluation based on real-world data shows that using suitable machine learning models effectively avoids over- and underallocation of resources, leading to up to 12 times lower resource consumption and better service quality with up to 4.5 times lower total delay than using standard fixed resource allocation.}}, author = {{Schneider, Stefan Balthasar and Satheeschandran, Narayanan Puthenpurayil and Peuster, Manuel and Karl, Holger}}, booktitle = {{IEEE Conference on Network Softwarization (NetSoft)}}, location = {{Ghent, Belgium}}, publisher = {{IEEE}}, title = {{{Machine Learning for Dynamic Resource Allocation in Network Function Virtualization}}}, year = {{2020}}, } @inproceedings{16222, author = {{Zafeiropoulos, A. and Fotopoulou, E. and Peuster, Manuel and Schneider, Stefan Balthasar and Gouvas, P. and Behnke, D. and Müller, M. and Bök, P. and Trakadas, P. and Karkazis, P. and Karl, Holger}}, booktitle = {{IEEE Conference on Network Softwarization (NetSoft)}}, title = {{{Benchmarking and Profiling 5G Verticals' Applications: An Industrial IoT Use Case}}}, year = {{2020}}, } @inproceedings{16400, abstract = {{Softwarization facilitates the introduction of smart manufacturing applications in the industry. Manifold devices such as machine computers, Industrial IoT devices, tablets, smartphones and smart glasses are integrated into factory networks to enable shop floor digitalization and big data analysis. To handle the increasing number of devices and the resulting traffic, a flexible and scalable factory network is necessary which can be realized using softwarization technologies like Network Function Virtualization (NFV). However, the security risks increase with the increasing number of new devices, so that cyber security must also be considered in NFV-based networks. Therefore, extending our previous work, we showcase threat detection using a cloud-native NFV-driven intrusion detection system (IDS) that is integrated in our industrial-specific network services. As a result of the threat detection, the affected network service is put into quarantine via automatic network reconfiguration. We use the 5GTANGO service platform to deploy our developed network services on Kubernetes and to initiate the network reconfiguration.}}, author = {{Müller, Marcel and Behnke, Daniel and Bök, Patrick-Benjamin and Schneider, Stefan Balthasar and Peuster, Manuel and Karl, Holger}}, booktitle = {{IEEE Conference on Network Softwarization (NetSoft) Demo Track}}, location = {{Ghent, Belgium}}, publisher = {{IEEE}}, title = {{{Cloud-Native Threat Detection and Containment for Smart Manufacturing}}}, year = {{2020}}, } @inproceedings{3287, abstract = {{For optimal placement and orchestration of network services, it is crucial that their structure and semantics are specified clearly and comprehensively and are available to an orchestrator. Existing specification approaches are either ambiguous or miss important aspects regarding the behavior of virtual network functions (VNFs) forming a service. We propose to formally and unambiguously specify the behavior of these functions and services using Queuing Petri Nets (QPNs). QPNs are an established method that allows to express queuing, synchronization, stochastically distributed processing delays, and changing traffic volume and characteristics at each VNF. With QPNs, multiple VNFs can be connected to complete network services in any structure, even specifying bidirectional network services containing loops. We discuss how management and orchestration systems can benefit from our clear and comprehensive specification approach, leading to better placement of VNFs and improved Quality of Service. Another benefit of formally specifying network services with QPNs are diverse analysis options, which allow valuable insights such as the distribution of end-to-end delay. We propose a tool-based workflow that supports the specification of network services and the automatic generation of corresponding simulation code to enable an in-depth analysis of their behavior and performance.}}, author = {{Schneider, Stefan Balthasar and Sharma, Arnab and Karl, Holger and Wehrheim, Heike}}, booktitle = {{2019 IFIP/IEEE International Symposium on Integrated Network Management (IM)}}, location = {{Washington, DC, USA}}, pages = {{116----124}}, publisher = {{IFIP}}, title = {{{Specifying and Analyzing Virtual Network Services Using Queuing Petri Nets}}}, year = {{2019}}, } @inproceedings{9270, abstract = {{As 5G and network function virtualization (NFV) are maturing, it becomes crucial to demonstrate their feasibility and benefits by means of vertical scenarios. While 5GPPP has identified smart manufacturing as one of the most important vertical industries, there is still a lack of specific, practical use cases. Using the experience from a large-scale manufacturing company, Weidm{\"u}ller Group, we present a detailed use case that reflects the needs of real-world manufacturers. We also propose an architecture with specific network services and virtual network functions (VNFs) that realize the use case in practice. As a proof of concept, we implement the required services and deploy them on an emulation-based prototyping platform. Our experimental results indicate that a fully virtualized smart manufacturing use case is not only feasible but also reduces machine interconnection and configuration time and thus improves productivity by orders of magnitude.}}, author = {{Schneider, Stefan Balthasar and Peuster, Manuel and Behnke, Daniel and Marcel, Müller and Bök, Patrick-Benjamin and Karl, Holger}}, booktitle = {{European Conference on Networks and Communications (EuCNC)}}, keywords = {{5g, vertical, smart manufacturing, nfv}}, publisher = {{IEEE}}, title = {{{Putting 5G into Production: Realizing a Smart Manufacturing Vertical Scenario}}}, doi = {{10.1109/eucnc.2019.8802016}}, year = {{2019}}, } @article{8113, abstract = {{The ongoing softwarization of networks creates a big need for automated testing solutions to ensure service quality. This becomes even more important if agile environments with short time to market and high demands, in terms of service performance and availability, are considered. In this paper, we introduce a novel testing solution for virtualized, microservice-based network functions and services, which we base on TTCN-3, a well known testing language defined by the European standards institute (ETSI). We use TTCN-3 not only for functional testing but also answer the question whether TTCN-3 can be used for performance profiling tasks as well. Finally, we demonstrate the proposed concepts and solutions in a case study using our open-source prototype to test and profile a chained network service.}}, author = {{Peuster, Manuel and Dröge, Christian and Boos, Clemens and Karl, Holger}}, issn = {{2405-9595}}, journal = {{ICT Express}}, publisher = {{Elsevier BV}}, title = {{{Joint testing and profiling of microservice-based network services using TTCN-3}}}, doi = {{10.1016/j.icte.2019.02.001}}, year = {{2019}}, } @inproceedings{8792, abstract = {{5G together with software defined networking (SDN) and network function virtualisation (NFV) will enable a wide variety of vertical use cases. One of them is the smart man- ufacturing case which utilises 5G networks to interconnect production machines, machine parks, and factory sites to enable new possibilities in terms of flexibility, automation, and novel applications (industry 4.0). However, the availability of realistic and practical proof-of-concepts for those smart manufacturing scenarios is still limited. This demo fills this gap by not only showing a real-world smart manufacturing application entirely implemented using NFV concepts, but also a lightweight prototyping framework that simplifies the realisation of vertical NFV proof-of-concepts. Dur- ing the demo, we show how an NFV-based smart manufacturing scenario can be specified, on-boarded, and instantiated before we demonstrate how the presented NFV services simplify machine data collection, aggregation, and analysis.}}, author = {{Peuster, Manuel and Schneider, Stefan Balthasar and Behnke, Daniel and Müller, Marcel and Bök, Patrick-Benjamin and Karl, Holger}}, booktitle = {{5th IEEE International Conference on Network Softwarization (NetSoft 2019)}}, location = {{Paris}}, title = {{{Prototyping and Demonstrating 5G Verticals: The Smart Manufacturing Case}}}, doi = {{10.1109/NETSOFT.2019.8806685}}, year = {{2019}}, } @article{8795, abstract = {{Softwarized networks are the key enabler for elastic, on-demand service deployments of virtualized network functions. They allow to dynamically steer traffic through the network when new network functions are instantiated, or old ones are terminated. These scenarios become in particular challenging when stateful functions are involved, necessitating state management solutions to migrate state between the functions. The problem with existing solutions is that they typically embrace state migration and flow rerouting jointly, imposing a huge set of requirements on the on-boarded virtualized network functions (VNFs), eg, solution-specific state management interfaces. To change this, we introduce the seamless handover protocol (SHarP). An easy-to-use, loss-less, and order-preserving flow rerouting mechanism that is not fixed to a single state management approach. Using SHarP, VNF vendors are empowered to implement or use the state management solution of their choice. SHarP supports these solutions with additional information when flows are migrated. In this paper, we present SHarP's design, its open source prototype implementation, and show how SHarP significantly reduces the buffer usage at a central (SDN) controller, which is a typical bottleneck in state-of-the-art solutions. Our experiments show that SHarP uses a constant amount of controller buffer, irrespective of the time taken to migrate the VNF state.}}, author = {{Peuster, Manuel and Küttner, Hannes and Karl, Holger}}, issn = {{1055-7148}}, journal = {{International Journal of Network Management}}, title = {{{A flow handover protocol to support state migration in softwarized networks}}}, doi = {{10.1002/nem.2067}}, year = {{2019}}, } @article{9823, author = {{Soenen, Thomas and Tavernier, Wouter and Peuster, Manuel and Vicens, Felipe and Xilouris, George and Kolometsos, Stavros and Kourtis, Michail-Alexandros and Colle, Didier}}, issn = {{0163-6804}}, journal = {{IEEE Communications Magazine}}, pages = {{89--95}}, title = {{{Empowering Network Service Developers: Enhanced NFV DevOps and Programmable MANO}}}, doi = {{10.1109/mcom.2019.1800810}}, year = {{2019}}, } @inproceedings{15368, abstract = {{Service Level Agreements are essential tools enabling clients and telco operators to specify required quality of service. The 5GTANGO NFV platform enables SLAs through policies and custom service lifecycle management components. This allows the operator to trigger certain lifecycle management events for a service, and the network service developer to define how to execute such events (e.g., how to scale). In this demo we will demonstrate this unique 5GTANGO concept using an elastic proxy service supported by a high availability SLA enforced through a range of traffic regimes.}}, author = {{Soenen, Thomas and Vicens, Felipe and Bonnet, José and Parada, Carlos and Kapassa, Evgenia and Touloupou, Marious and Fotopulou, Eleni and Zafeiropoulos, Anastasios and Pol, Ana and Kolometsos, Stavros and Xilouris, George and Alemany, Pol and Vilalta, Ricard and Trakadas, Panos and Karkazis, Panos and Peuster, Manuel and Tavernier, Wouter}}, booktitle = {{2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)}}, issn = {{1573-0077}}, keywords = {{5G mobile communication, contracts, quality of service, telecommunication traffic, virtualisation, custom service lifecycle management components, lifecycle management events, network service developer, elastic proxy service, SLA-controlled proxy service, customisable MANO, operator policies, Service Level Agreements, unique 5G TANGO concept, 5G TANGO NFV platform, quality of service, traffic regimes, high availability SLA, Monitoring, Probes, Portals, Quality of service, Tools, Servers, Graphical user interfaces}}, location = {{Arlington, VA, USA, USA}}, pages = {{707--708}}, title = {{{SLA-controlled Proxy Service Through Customisable MANO Supporting Operator Policies}}}, year = {{2019}}, } @inproceedings{15369, author = {{Müller, Marcel and Behnke, Daniel and Bök, Patrick-Benjamin and Peuster, Manuel and Schneider, Stefan Balthasar and Karl, Holger}}, booktitle = {{IEEE 17th International Conference on Industrial Informatics (IEEE-INDIN)}}, publisher = {{IEEE}}, title = {{{5G as Key Technology for Networked Factories: Application of Vertical-specific Network Services for Enabling Flexible Smart Manufacturing}}}, year = {{2019}}, } @inproceedings{15371, abstract = {{More and more management and orchestration approaches for (software) networks are based on machine learning paradigms and solutions. These approaches depend not only on their program code to operate properly, but also require enough input data to train their internal models. However, such training data is barely available for the software networking domain and most presented solutions rely on their own, sometimes not even published, data sets. This makes it hard, or even infeasible, to reproduce and compare many of the existing solutions. As a result, it ultimately slows down the adoption of machine learning approaches in softwarised networks. To this end, we introduce the "softwarised network data zoo" (SNDZoo), an open collection of software networking data sets aiming to streamline and ease machine learning research in the software networking domain. We present a general methodology to collect, archive, and publish those data sets for use by other researches and, as an example, eight initial data sets, focusing on the performance of virtualised network functions. }}, author = {{Peuster, Manuel and Schneider, Stefan Balthasar and Karl, Holger}}, booktitle = {{IEEE/IFIP 15th International Conference on Network and Service Management (CNSM)}}, publisher = {{IEEE/IFIP}}, title = {{{The Softwarised Network Data Zoo}}}, year = {{2019}}, } @inproceedings{15372, author = {{Nuriddinov, Askhat and Tavernier, Wouter and Colle, Didier and Pickavet, Mario and Peuster, Manuel and Schneider, Stefan Balthasar}}, booktitle = {{ IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)}}, publisher = {{IEEE}}, title = {{{Reproducible Functional Tests for Multi-scale Network Services}}}, year = {{2019}}, } @inproceedings{15373, abstract = {{Offloading packet processing tasks to programmable switches and/or to programmable network interfaces, so called “SmartNICs”, is one of the key concepts to prepare softwarized networks for the high traffic demands of the future. However, implementing network functions that make use of those offload- ing technologies is still challenging and usually requires the availability of specialized hardware. It becomes even harder if heterogeneous services, making use of different offloading and network virtualization technologies, should be developed. In this paper, we introduce FOP4 (Function Offloading Pro- totyping with P4), a novel prototyping platform that allows to prototype heterogeneous software network scenarios, including container-based, P4-switch-based, and SmartNIC-based network functions. The presented work substantially extends our existing Containernet platform with the means to prototype offloading scenarios. Besides presenting the platform’s system design, we evaluate its scalability and show that it can run scenarios with more than 64 P4 switch or SmartNIC nodes on a single laptop. Finally, we presented a case study in which we use the presented platform to prototype an extended in-band network telemetry use case.}}, author = {{Moro, Daniele and Peuster, Manuel and Karl, Holger and Capone, Antonio}}, booktitle = {{IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)}}, publisher = {{IEEE}}, title = {{{FOP4: Function Offloading Prototyping in Heterogeneous and Programmable Network Scenarios}}}, year = {{2019}}, } @inproceedings{15375, author = {{Müller, Marcel and Behnke, Daniel and Bök, Patrick-Benjamin and Schneider, Stefan Balthasar and Peuster, Manuel and Karl, Holger}}, booktitle = {{IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)}}, publisher = {{IEEE}}, title = {{{Putting NFV into Reality: Physical Smart Manufacturing Testbed}}}, year = {{2019}}, } @inproceedings{15376, author = {{Behnke, Daniel and Müller, Marcel and Bök, Patrick-Benjamin and Schneider, Stefan Balthasar and Peuster, Manuel and Karl, Holger}}, booktitle = {{IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)}}, publisher = {{IEEE}}, title = {{{NFV-driven intrusion detection for smart manufacturing}}}, year = {{2019}}, } @inproceedings{13292, abstract = {{Building on 5G and network function virtualization (NFV), smart manufacturing has the potential to drastically increase productivity, reduce cost, and introduce novel, flexible manufacturing services. Current work mostly focuses on high-level scenarios or emulation-based prototype deployments. Extending our previous work, we showcase one of the first cloud-native 5G verticals focusing on the deployment of smart manufacturing use cases on production infrastructure. In particular, we use the 5GTANGO service platform to deploy our developed network services on Kubernetes. For this demo, we implemented a series of cloud-native virtualized network functions (VNFs) and created suitable service descriptors. Their light-weight, stateless deployment on Kubernetes enables quick instantiation, scalability, and robustness.}}, author = {{Schneider, Stefan Balthasar and Peuster, Manuel and Hannemann, Kai and Behnke, Daniel and Müller, Marcel and Bök, Patrick-Benjamin and Karl, Holger}}, booktitle = {{IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) Demo Track}}, keywords = {{5G, NFV, Smart Manufacturing, Cloud-Native, Kubernetes}}, location = {{Dallas, TX, USA}}, publisher = {{IEEE}}, title = {{{"Producing Cloud-Native": Smart Manufacturing Use Cases on Kubernetes}}}, year = {{2019}}, } @article{10325, author = {{Peuster, Manuel and Marchetti, Michael and García de Blas, Gerardo and Karl, Holger}}, issn = {{1687-1499}}, journal = {{EURASIP Journal on Wireless Communications and Networking}}, publisher = {{Springer}}, title = {{{Automated testing of NFV orchestrators against carrier-grade multi-PoP scenarios using emulation-based smoke testing}}}, doi = {{10.1186/s13638-019-1493-2}}, year = {{2019}}, } @inproceedings{2481, abstract = {{Network function virtualization requires scaling and placement, deciding the number and the location of function instances. Current approaches are limited in flexibility and practical applicability. Specifically, we study dynamic, single-step, joint scaling and placement of network services with bidirectional flows traversing Physical or Virtual Network Functions (VNFs) and returning to their sources. We develop models to support stateful components and legacy network functions with fixed locations in these network services as well as the possibility of reusing VNFs across network services. We formalize the problem of jointly scaling and placing such network services as a mixed- integer linear program (MILP). We show that this problem is NP-complete and also present a heuristic algorithm to find good solutions in short time. In an extensive evaluation with realistic scenarios, we investigate the capabilities of the two approaches.}}, author = {{Dräxler, Sevil and Schneider, Stefan Balthasar and Karl, Holger}}, booktitle = {{4th IEEE International Conference on Network Softwarization (NetSoft 2018)}}, location = {{Montreal}}, pages = {{123----131}}, publisher = {{IEEE}}, title = {{{ Scaling and Placing Bidirectional Services with Stateful Virtual and Physical Network Functions}}}, year = {{2018}}, } @inproceedings{3345, abstract = {{Dynamically steering flows through virtualized net- work function instances is a key enabler for elastic, on-demand deployments of virtualized network functions. This becomes par- ticular challenging when stateful functions are involved, necessi- tating state management. The problem with existing solutions is that they typically embrace state migration and flow rerouting jointly, imposing a huge set of requirements on the on-boarded VNFs, e.g., solution-specific state management interfaces. In this paper, we introduce the seamless handover proto- col (SHarP). It provides an easy-to-use, loss-less, and order- preserving flow rerouting mechanism that is not fixed to a single state management approach. This allows VNF vendors to implement or use the state management solution of their choice. SHarP supports these solutions with additional information when flows are migrated. Further, we show how SHarP significantly reduces the buffer usage at a central (SDN) controller, which is a typical bottleneck in existing solutions. Our experiments show that SHarP uses a constant amount of controller buffer, irrespective of the time taken to migrate the VNF state.}}, author = {{Peuster, Manuel and Küttner, Hannes and Karl, Holger}}, booktitle = {{4th IEEE International Conference on Network Softwarization (NetSoft 2018)}}, location = {{Montreal}}, title = {{{ Let the state follow its flows: An SDN-based flow handover protocol to support state migration}}}, doi = {{10.1109/NETSOFT.2018.8460007}}, year = {{2018}}, }