@inproceedings{983,
  author       = {{Auroux, Sébastien and Scholz, S. and Karl, Holger}},
  booktitle    = {{Proc. European Wireless}},
  title        = {{{Assessing Genetic Algorithms for Placing Flow Processing-aware Control Applications}}},
  year         = {{2017}},
}

@inproceedings{1618,
  author       = {{Zhao, Mengxuan and Le Gall, Franck and Cousin, Philippe and Vilalta, Ricard and Munoz, Raul and Castro, Sonia and Peuster, Manuel and Schneider, Stefan Balthasar and Siapera, Maria and Kapassa, Evgenia and Kyriazis, Dimosthenis and Hasselmeyer, Peer and Xilouris, George and Tranoris, Christos and Denazis, Spyros and Martrat, Josep}},
  booktitle    = {{2017 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)}},
  isbn         = {{9781538632857}},
  publisher    = {{IEEE}},
  title        = {{{Verification and validation framework for 5G network services and apps}}},
  doi          = {{10.1109/nfv-sdn.2017.8169878}},
  year         = {{2017}},
}

@inproceedings{1620,
  author       = {{Aktas, Ismet and Ansari, Junaid and Auroux, Sebastien and Parruca, Donald and Perez Guirao, Maria Dolores and Holfeld, Bernd}},
  publisher    = {{Proceedings of 23th European Wireless Conference}},
  title        = {{{A Coordination Architecture for Wireless Industrial Automation}}},
  year         = {{2017}},
}

@phdthesis{220,
  author       = {{Keller, Matthias}},
  publisher    = {{Universität Paderborn}},
  title        = {{{Application Deployment at Distributed Clouds}}},
  year         = {{2016}},
}

@article{714,
  abstract     = {{The Service Programming and Orchestration for Virtualised Software Networks (SONATA) project targets both the flexible programmability of software networks and the optimisation of their deployments by means of integrating Development and Operations in order to accelerate industry adoption of software networks and reduce time-to-market for networked services. SONATA supports network function chaining and orchestration, making service platforms modular and easier to customise to the needs of different service providers, and introduces a specialised Development and Operations model for supporting developers.}},
  author       = {{Karl, Holger and Dräxler, Sevil and Peuster, Manuel and Galis, Alex and Bredel, Michael and Ramos, Aurora and Martrat, Josep and Siddiqui, Muhammad Shuaib and van Rossem, Steven and Tavernier, Wouter and Xilouris, George}},
  issn         = {{2161-3915}},
  journal      = {{Transactions on Emerging Telecommunications Technologies}},
  number       = {{9}},
  pages        = {{1206--1215}},
  publisher    = {{Wiley-Blackwell}},
  title        = {{{DevOps for network function virtualisation: an architectural approach}}},
  doi          = {{10.1002/ett.3084}},
  volume       = {{27}},
  year         = {{2016}},
}

@article{726,
  author       = {{Wette, Philip and Karl, Holger}},
  journal      = {{Computer Communications}},
  pages        = {{45----58}},
  title        = {{{DCT²Gen: A traffic generator for data centers}}},
  doi          = {{10.1016/j.comcom.2015.12.001}},
  year         = {{2016}},
}

@inproceedings{728,
  author       = {{Schwabe, Arne and A. Aranda-Gutierrez, Pedro and Karl, Holger}},
  booktitle    = {{Proceedings of the 2016 Applied Networking Research Workshop, {ANRW} 2016, Berlin, Germany, July 16, 2016}},
  pages        = {{26----31}},
  title        = {{{Composition of SDN applications: Options/challenges for real implementations}}},
  doi          = {{10.1145/2959424.2959436}},
  year         = {{2016}},
}

@inproceedings{729,
  author       = {{Doriguzzi Corin, Roberto and A. Aranda-Gutierrez, Pedro and Rojas, Elisa and Karl, Holger and Salvadori, Elio}},
  booktitle    = {{12th International Conference on Network and Service Management, {CNSM} 2016, Montreal, QC, Canada, October 31 - Nov. 4, 2016}},
  pages        = {{209----215}},
  title        = {{{Reusability of software-defined networking applications: {A} runtime, multi-controller approach}}},
  doi          = {{10.1109/CNSM.2016.7818419}},
  year         = {{2016}},
}

@inproceedings{730,
  abstract     = {{Allocating resources to virtualized network functions and services to meet service level agreements is a challenging task for NFV management and orchestration systems. This becomes even more challenging when agile development methodologies, like DevOps, are applied. In such scenarios, management and orchestration systems are continuously facing new versions of functions and services which makes it hard to decide how much resources have to be allocated to them to provide the expected service performance. 
One solution for this problem is to support resource allocation decisions with performance behavior information obtained by profiling techniques applied to such network functions and services.

In this position paper, we analyze and discuss the components needed to generate such performance behavior information within the NFV DevOps workflow. We also outline research questions that identify open issues and missing pieces for a fully integrated NFV profiling solution. Further, we introduce a novel profiling mechanism that is able to profile virtualized network functions and entire network service chains under different resource constraints before they are deployed on production infrastructure.}},
  author       = {{Peuster, Manuel and Karl, Holger}},
  booktitle    = {{Fifth European Workshop on Software-Defined Networks, EWSDN 2016, Den Haag, The Netherlands, October 10-11, 2016}},
  location     = {{Den Haag}},
  pages        = {{7----12}},
  title        = {{{Understand Your Chains: Towards Performance Profile-Based Network Service Management}}},
  doi          = {{10.1109/EWSDN.2016.9}},
  year         = {{2016}},
}

@inproceedings{731,
  abstract     = {{Traditional cellular networks are forced to remain active regardless of the actual amount of traffic that is currently produced/requested, with a clear waste of energy. Two-layer mobile networks with separated signalling and data layers have been recently proposed for energy savings in future implementations. These networks are able to switch off unneeded data cells completely while maintaining full coverage with their signalling cells, thus saving energy. In this demonstration, we showcase a testbed that uses Wi-Fi access points to emulate small cells of the data layer and a publicly available cellular connection as the signalling layer. We use off-the-shelf Android smartphones with an ad-hoc networking management module and a MultiPath TCP-enabled kernel to manage the Wi-Fi and cellular interfaces simultaneously.
The testbed is used to demonstrate the general feasibility of this layered architecture and to facilitate experiments with network-wide resource optimization. }},
  author       = {{Peuster, Manuel and Karl, Holger and Enrico Redondi, Alessandro and Capone, Antonio}},
  booktitle    = {{IEEE Conference on Computer Communications Workshops, INFOCOM Workshops 2016, San Francisco, CA, USA, April 10-14, 2016}},
  location     = {{San Francisco}},
  pages        = {{1015----1016}},
  title        = {{{Demonstrating on-demand cell switching with a two-layer mobile network testbed}}},
  doi          = {{10.1109/INFCOMW.2016.7562232}},
  year         = {{2016}},
}

@inproceedings{732,
  abstract     = {{Elastic deployments of virtualized network functions~(VNF) can automatically scale the amount of used resources in relation to their workload. This is often done by starting new VNF instances or stopping old ones. A problem of these scale operations is that most network functions are stateful and their internal state is not automatically migrated when traffic is redistributed in the deployment. As a result, mechanisms are needed to exchange or migrate internal network function state between VNF instances.

This paper presents a state management framework that creates a logically distributed state store on top of elastically deployed virtual network functions. We also introduce a novel programming model that provides both a local and a global view of the state to each VNF instance. We discuss the integration of our framework into existing network function virtualization architectures and compare the performance of our prototype to a centralized and a distributed state store solution.}},
  author       = {{Peuster, Manuel and Karl, Holger}},
  booktitle    = {{IEEE NetSoft Conference and Workshops, NetSoft 2016, Seoul, South Korea, June 6-10, 2016}},
  location     = {{Seoul}},
  pages        = {{6----10}},
  title        = {{{E-State: Distributed state management in elastic network function deployments}}},
  doi          = {{10.1109/NETSOFT.2016.7502432}},
  year         = {{2016}},
}

@inproceedings{735,
  author       = {{Auroux, Sébastien and Parruca, Donald and Karl, Holger}},
  booktitle    = {{27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, {PIMRC} 2016, Valencia, Spain, September 4-8, 2016}},
  pages        = {{1----6}},
  title        = {{{Joint real-time scheduling and interference coordination for wireless factory automation}}},
  doi          = {{10.1109/PIMRC.2016.7794927}},
  year         = {{2016}},
}

@inproceedings{738,
  abstract     = {{Virtualized network services consisting of multiple individual network functions are already today deployed across multiple sites, so called multi-PoP (points of presence) environments. This allows to improve service performance by optimizing its placement in the network. But prototyping and testing of these complex distributed software systems becomes extremely challenging. The reason is that not only the network service as such has to be tested but also its integration with management and orchestration systems. Existing solutions, like simulators, basic network emulators, or local cloud testbeds, do not support all aspects of these tasks.

To this end, we introduce MeDICINE, a novel NFV prototyping platform that is able to execute production-ready network functions, provided as software containers, in an emulated multi-PoP environment. These network functions can be controlled by any third-party management and orchestration system that connects to our platform through standard interfaces. Based on this, a developer can use our platform to prototype and test complex network services in a realistic environment running on his laptop.
}},
  author       = {{Peuster, Manuel and Karl, Holger and van Rossem, Steven}},
  booktitle    = {{IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)}},
  location     = {{Palo Alto}},
  title        = {{{MeDICINE: Rapid Prototyping of Production-Ready Network Services in Multi-PoP Environments}}},
  doi          = {{10.1109/NFV-SDN.2016.7919490}},
  year         = {{2016}},
}

@inproceedings{985,
  author       = {{v. Rossem, S. and Tavernier, W. and Peuster, Manuel and Colle, D. and Pickavet, M. and Demeester, P.}},
  booktitle    = {{Proc. IEEE Conference on Network Function Virtualization and Software Defined Network (NFV-SDN), Demo Track}},
  title        = {{{Monitoring and debugging using an SDK for NFV-powered telecom applications}}},
  year         = {{2016}},
}

@inproceedings{166,
  abstract     = {{Network function virtualization and software-defined networking allow services consisting of virtual network functions to be designed and implemented with great flexibility by facilitating automatic deployments, migrations, and reconfigurations for services and their components. For extended flexibility, we go beyond seeing services as a fixed chain of functions. We present a YANG model for describing the service structure in deployment requests in a flexible way that enables changing the order of functions in case the order of traversing them does not affect the functionality of the service. Upon receiving such requests, the network orchestration system can choose the optimal composition of service components that gives the best results for placement of services in the network. This introduces new complexities to the placement problem by greatly increasing the number of possible ways a service can be composed. In this paper, we describe a heuristic solution that selects a Pareto set of the possible compositions of a service as well as possible combinations of different services, with respect to different resource requirements of the services. Our evaluations show that the selected combinations consist of representative samples of possible structures and requirements and therefore, can result in optimal or close-to-optimal placement results.}},
  author       = {{Dräxler, Sevil and Karl, Holger}},
  booktitle    = {{Proceedings of the 2nd International IEEE Conference on Network Softwarization (NetSoft)}},
  pages        = {{184----192}},
  title        = {{{Placement of Services with Flexible Structures Specified by a YANG Data Model}}},
  doi          = {{10.1109/NETSOFT.2016.7502412}},
  year         = {{2016}},
}

@inproceedings{1627,
  author       = {{Gutierrez, P. A. Aranda and Rojas, E. and Schwabe, A. and Stritzke, C. and Doriguzzi-Corin, R. and Leckey, A. and Petralia, G. and Marsico, A. and Phemius, K. and Tamurejo, S.}},
  booktitle    = {{2016 IEEE NetSoft Conference and Workshops (NetSoft)}},
  isbn         = {{9781467394864}},
  publisher    = {{IEEE}},
  title        = {{{NetIDE: All-in-one framework for next generation, composed SDN applications}}},
  doi          = {{10.1109/netsoft.2016.7502408}},
  year         = {{2016}},
}

@inproceedings{1630,
  author       = {{Marsico, Antonio and Doriguzzi-Corin, Roberto and Gerola, Matteo and Siracusa, Domenico and Schwabe, Arne}},
  booktitle    = {{NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium}},
  isbn         = {{9781509002238}},
  publisher    = {{IEEE}},
  title        = {{{A non-disruptive automated approach to update SDN applications at runtime}}},
  doi          = {{10.1109/noms.2016.7502946}},
  year         = {{2016}},
}

@inproceedings{1632,
  author       = {{Doriguzzi-Corin, Roberto and Siracusa, Domenico and Salvador, Elio and Schwabe, Arne}},
  booktitle    = {{NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium}},
  isbn         = {{9781509002238}},
  publisher    = {{IEEE}},
  title        = {{{Empowering network operating systems with memory management techniques}}},
  doi          = {{10.1109/noms.2016.7502889}},
  year         = {{2016}},
}

@article{1373,
  author       = {{Herlich, Matthias and Bredenbals, Nico and Karl, Holger}},
  issn         = {{2210-5379}},
  journal      = {{Sustainable Computing: Informatics and Systems}},
  pages        = {{48--55}},
  publisher    = {{Elsevier BV}},
  title        = {{{Delayed (de-)activation in servers with a sleep mode}}},
  doi          = {{10.1016/j.suscom.2016.04.002}},
  volume       = {{10}},
  year         = {{2016}},
}

@inproceedings{252,
  abstract     = {{Video streaming is in high demand by mobile users. In cellular networks, however, the unreliable wireless channel leads to two major problems. Poor channel states degrade video quality and interrupt the playback when a user cannot sufficiently fill its local playout buffer: buffer underruns occur. In contrast, good channel conditions cause common greedy buffering schemes to buffer too much data. Such over-buffering wastes expensive wireless channel capacity. Assuming that we can anticipate future data rates, we plan the quality and download time of video segments ahead. This anticipatory download scheduling avoids buffer underruns by downloading a large number of segments before a drop in available data rate occurs, without wasting wireless capacity by excessive buffering.We developed a practical anticipatory scheduling algorithm for segmented video streaming protocols (e.g., HLS or MPEG DASH). Simulation results and testbed measurements show that our solution essentially eliminates playback interruptions without significantly decreasing video quality.}},
  author       = {{Dräxler, Martin and Blobel, Johannes and Dreimann, Philipp and Valentin, Stefan and Karl, Holger}},
  booktitle    = {{Proceedings of the 2nd International Conference on Networked Systems (NetSys)}},
  pages        = {{1----8}},
  title        = {{{SmarterPhones: Anticipatory Download Scheduling for Wireless Video Streaming}}},
  doi          = {{10.1109/NetSys.2015.7089073}},
  year         = {{2015}},
}

