Consensus algorithms in distributed SDN controllers

Software defined networks (SDN) promise greater flexibility, cost efficiency and easier management of network infrastructure by logically centralizing the control and abstracting network resources, but their wider use is inhibited by various challenges. In this master’s thesis, we explore the problem of ensuring high-availability of SDN controllers. It is a mostly unexplored problem which is also crucial with the implementation of software defined networks in production environments. Firstly, we present the concept of software defined networking. Doing so, we explore where their use has the greatest potential and identify various challenges which make their implementation difficult. We emphasize the problem of ensuring high-availability and the scalability of the network because of the centralized control plane and list as a solution the implementation of a controller in the form of a fault-tolerant distributed system. Following this, we study the limitations in design and the implementation of these systems. We focus on consensus algorithms as a key component in ensuring high availability. Following this, we present strategies with developing distributed controllers and explore which open-source implementations allow for their high availability. We choose the ONOS controller as the potentially most suitable for production use and analyze its architecture. With the chosen controller and the simulator of software defined networks Mininet, we establish a pilot environment. We develop a test framework for simulating scenarios that include various controller node and communication channel failures and analyze system behavior while doing so. Based on the results of the analysis we evaluate the chosen controller implementation based on ensuring high availability and give suggestions for improving the availability of the solution

Simplification of Internet Ossification through Software Defined Network Approach

Software-Defined Networking (SDN) has received a great deal of attention from both academia and industry in recent years. Studies on SDN have brought a number of interesting technical discussions on network architecture design, along with scientific contributions. Researchers, network operators, and vendors are trying to establish new standards and provide guidelines for proper implementation and deployment of such novel approach. It is clear that many of these research efforts have been made in the southbound of the SDN architecture, while the northbound interface still needs improvements. By focusing in the SDN northbound, this paper surveys the body of knowledge and discusses the challenges for developing SDN software. We investigate the existing solutions and identify trends and challenges on programming for SDN environments. We also discuss future developments on techniques, specifications, and methodologies for programmable networks, with the orthogonal view from the Software Engineering discipline

The Challenges in SDN/ML Based Network Security : A Survey

Machine Learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking (SDN) emerge. Sitting at the application layer and communicating with the control layer, machine learning based SDN security models exercise a huge influence on the routing/switching of the entire SDN. Compromising the models is consequently a very desirable goal. Previous surveys have been done on either adversarial machine learning or the general vulnerabilities of SDNs but not both. Through examination of the latest ML-based SDN security applications and a good look at ML/SDN specific vulnerabilities accompanied by common attack methods on ML, this paper serves as a unique survey, making a case for more secure development processes of ML-based SDN security applications.Comment: 8 pages. arXiv admin note: substantial text overlap with arXiv:1705.0056

Migration cost optimization for service provider legacy network migration to software-defined IPv6 network

This is the peer reviewed version of the following article: Dawadi, BR, Rawat, DB, Joshi, SR, Manzoni, P, Keitsch, MM. Migration cost optimization for service provider legacy network migration to software-defined IPv6 network. Int J Network Mgmt. 2021; 31:e2145, which has been published in final form at https://doi.org/10.1002/nem.2145. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] This paper studies a problem for seamless migration of legacy networks of Internet service providers to a software-defined networking (SDN)-based architecture along with the transition to the full adoption of the Internet protocol version 6 (IPv6) connectivity. Migration of currently running legacy IPv4 networks into such new approaches requires either upgrades or replacement of existing networking devices and technologies that are actively operating. The joint migration to SDN and IPv6 network is considered to be vital in terms of migration cost optimization, skilled human resource management, and other critical factors. In this work, we first present the approaches of SDN and IPv6 migration in service providers' networks. Then, we present the common concerns of IPv6 and SDN migration with joint transition strategies so that the cost associated with joint migration is minimized to lower than that of the individual migration. For the incremental adoption of software-defined IPv6 (SoDIP6) network with optimum migration cost, a greedy algorithm is proposed based on optimal path and the customer priority. Simulation and empirical analysis show that a unified transition planning to SoDIP6 network results in lower migration cost.U.S. National Science Foundation (NSF), Grant/Award Number: CNS 1650831 and HRD 1828811; ERASMUS+ KA107; Nepal Academy of Science and Technology (NAST); Norwegian University of Science and Technology; University Grant Commission (UGC), Nepal, Grant/Award Number: FRG/74_75/Engg-1Dawadi, BR.; Rawat, DB.; Joshi, SR.; Manzoni, P.; Keitsch, MM. (2021). Migration cost optimization for service provider legacy network migration to software-defined IPv6 network. International Journal of Network Management. 31(4):1-24. https://doi.org/10.1002/nem.2145S124314APNIC.IPv6 capability measurement.https://stats.labs.apnic.net/ipv6. Accessed April 22 2020.Google Incl. IPv6 user access status.https://www.google.com/intl/en/ipv6/statistics.html. Accessed February 16 2020.Rawat, D. B., & Reddy, S. R. (2017). Software Defined Networking Architecture, Security and Energy Efficiency: A Survey. IEEE Communications Surveys & Tutorials, 19(1), 325-346. doi:10.1109/comst.2016.2618874Dai, B., Xu, G., Huang, B., Qin, P., & Xu, Y. (2017). Enabling network innovation in data center networks with software defined networking: A survey. Journal of Network and Computer Applications, 94, 33-49. doi:10.1016/j.jnca.2017.07.004Kobayashi, M., Seetharaman, S., Parulkar, G., Appenzeller, G., Little, J., van Reijendam, J., … McKeown, N. (2014). Maturing of OpenFlow and Software-defined Networking through deployments. Computer Networks, 61, 151-175. doi:10.1016/j.bjp.2013.10.011Gumaste, A., Sharma, V., Kakadia, D., Yates, J., Clauberg, A., & Voltolini, M. (2017). SDN Use Cases for Service Provider Networks: Part 2. IEEE Communications Magazine, 55(4), 62-63. doi:10.1109/mcom.2017.7901478Dawadi, B. R., Rawat, D. B., & Joshi, S. R. (2019). Software Defined IPv6 Network: A New Paradigm for Future Networking. Journal of the Institute of Engineering, 15(2), 1-13. doi:10.3126/jie.v15i2.27636Shah, J. L., Bhat, H. F., & Khan, A. I. (2019). Towards IPv6 Migration and Challenges. International Journal of Technology Diffusion, 10(2), 83-96. doi:10.4018/ijtd.2019040105Rojas, E., Doriguzzi-Corin, R., Tamurejo, S., Beato, A., Schwabe, A., Phemius, K., & Guerrero, C. (2018). Are We Ready to Drive Software-Defined Networks? A Comprehensive Survey on Management Tools and Techniques. ACM Computing Surveys, 51(2), 1-35. doi:10.1145/3165290Contreras, L. M., Doolan, P., Lønsethagen, H., & López, D. R. (2015). Operational, organizational and business challenges for network operators in the context of SDN and NFV. Computer Networks, 92, 211-217. doi:10.1016/j.comnet.2015.07.016Amin, R., Reisslein, M., & Shah, N. (2018). Hybrid SDN Networks: A Survey of Existing Approaches. IEEE Communications Surveys & Tutorials, 20(4), 3259-3306. doi:10.1109/comst.2018.2837161Audi Marc Amjad A.The Advancement in Information and Communication Technologies (ICT) and Economic Development: A Panel Analysis. MPRA.https://mpra.ub.uni-muenchen.de/93476/. Published 2019. Accessed November 29 2019.Main, A., Zakaria, N. A., & Yusof, R. (2015). Organisation Readiness Factors Towards IPv6 Migration: Expert Review. Procedia - Social and Behavioral Sciences, 195, 1882-1889. doi:10.1016/j.sbspro.2015.06.427Dawadi, B. R., Rawat, D. B., Joshi, S. R., & Baral, D. S. (2019). Affordable Broadband with Software Defined IPv6 Network for Developing Rural Communities. Applied System Innovation, 3(1), 4. doi:10.3390/asi3010004Nikkhah, M. (2016). Maintaining the progress of IPv6 adoption. Computer Networks, 102, 50-69. doi:10.1016/j.comnet.2016.02.027Dell, P. (2018). On the dual-stacking transition to IPv6: A forlorn hope? Telecommunications Policy, 42(7), 575-581. doi:10.1016/j.telpol.2018.04.005GilliganRE NordmarkE GilliganRE et alBasic Transition Mechanisms for IPv6 Hosts and Routers.2000.Cui, Y., Dong, J., Wu, P., Wu, J., Metz, C., Lee, Y. L., & Durand, A. (2013). Tunnel-Based IPv6 Transition. IEEE Internet Computing, 17(2), 62-68. doi:10.1109/mic.2012.63BlanchetM ParentF.IPv6 Tunnel Broker with the Tunnel Setup Protocol (TSP).2010.HuitemaC.Teredo: Tunneling IPv6 over UDP through Network Address Translations (NATs) RFC 4380.2006.CarpenterB MooreK.Connection of IPv6 domains via IPv4 clouds.2001.JungC CarpenterBE.Transmission of IPv6 over IPv4 Domains without Explicit Tunnels.1999.CuiY WuJ LeeY WuP VautrinO.Public IPv4‐over‐IPv6 access Network2013.CuiY SunQ LeeYL TsouT FarrerI BoucadairM.Lightweight 4over6: an extension to the dual‐stack lite Architecture2015.TemplinF GleesonT TalwarM ThalerD.Intra‐Site Automatic Tunnel Addressing Protocol (ISATAP) RFC 5214.2008.DurandA DromsR WoodyattJ LeeY.RFC 6333: Dual‐Stack Lite Broadband Deployments Following IPv4 Exhaustion. IETF Aug.2011.BaoC DecW LiX TroanO MatsushimaS MurakamiT.Mapping of Address and Port with Encapsulation (MAP‐E). IETF Internet Draft.2015.TownsleyW TroanO.IPv6 Rapid Deployment on IPv4 Infrastructures (6rd)‐‐Protocol Specification.2010.ChenM ChenG JiangS LeeY DespresR PennoR.IPv4 Residual Deployment via IPv6‐A Stateless Solution (4rd).2015.WuP CuiY XuM et alPET: Prefixing encapsulation and translation for IPv4‐IPv6 coexistence. In: 2010IEEE Global Telecommunications Conference GLOBECOM2010. 2010:1–5.LiX BaoC ChenM ZhangH WuJ.IVI translation design and deployment for the IPv4/IPv6 coexistence and transition.IETF RFC6219 Internet Eng Task Force Fremont CA.2011.Bagnulo, M., Garcia-Martinez, A., & Van Beijnum, I. (2012). The NAT64/DNS64 tool suite for IPv6 transition. IEEE Communications Magazine, 50(7), 177-183. doi:10.1109/mcom.2012.6231295BagnuloM SullivanA MatthewsP VanBeijnumI.DNS64: DNS extensions for network address translation from IPv6 clients to IPv4 servers RFC 6147.2011.LiuD DengH.NAT46 Considerations.2010.MawatariM KawashimaM ByrneC.464XLAT: Combination of stateful and stateless translation. IETF Internet‐Draft.2013.PerreaultS YamagataI MiyakawaS NakagawaA.Common Requirements for Carrier‐Grade NATs (CGNs) RFC6888.2013.YamaguchiJ ShirasakiY NakagawaA AshidaH.Nat444 addressing models. Req Comments Draft Internet Eng Task Force.2012.ChenG CaoZ XieC BinetD.NAT64 Deployment Options and Experience RFC 7269.2014.LiX BaoC DecW TroanO MatsushimaS MurakamiT.Mapping of Address and Port using Translation (MAP‐T) RFC 7599. IETF Internet Draft.2013.Wu, P., Cui, Y., Wu, J., Liu, J., & Metz, C. (2013). Transition from IPv4 to IPv6: A State-of-the-Art Survey. IEEE Communications Surveys & Tutorials, 15(3), 1407-1424. doi:10.1109/surv.2012.110112.00200Hernandez-Valencia, E., Izzo, S., & Polonsky, B. (2015). How will NFV/SDN transform service provider opex? IEEE Network, 29(3), 60-67. doi:10.1109/mnet.2015.7113227BogineniK et alThe Open Networking Lab (ON.Lab). Introducing ONOS—a SDN network operating system for Service Providers.White Pap.2014;1:14.http://onosproject.org/wp-content/uploads/2014/11/Whitepaper-ONOS-final.pdfTR‐506 O ONF TR‐506.SDN Migration Considerations and Use Cases.2014.https://www.opennetworking.org/wp-content/uploads/2014/10/sb-sdn-migration-use-cases.pdfRisdiantoAC LingTC TsaiP YangC KimJ.Leveraging open‐source software for federated multisite SDN‐cloud playground. In: 2016 IEEE NetSoft Conference and Workshops (NetSoft). ;2016:423‐427.https://doi.org/10.1109/NETSOFT.2016.7502479GalizaH SchwarzM BezerraJ IbarraJ.Moving an ip network to sdn: a global use case deployment experience at amlight. In:Anais Do WPEIF2016Workshop de Pesquisa Experimental Da Internet Do Futuro: 15.LevinD CaniniM SchmidS SchaffertF Feldmann A.Panopticon: Reaping the Benefits of Incremental {SDN} Deployment in Enterprise Networks. In: 2014 {USENIX} Annual Technical Conference ({USENIX}{ATC} 14). ;2014:333–345.Vissicchio, S., Tilmans, O., Vanbever, L., & Rexford, J. (2015). Central Control Over Distributed Routing. ACM SIGCOMM Computer Communication Review, 45(4), 43-56. doi:10.1145/2829988.2787497Huang, X., Cheng, S., Cao, K., Cong, P., Wei, T., & Hu, S. (2019). A Survey of Deployment Solutions and Optimization Strategies for Hybrid SDN Networks. IEEE Communications Surveys & Tutorials, 21(2), 1483-1507. doi:10.1109/comst.2018.2871061Csikor, L., Szalay, M., Retvari, G., Pongracz, G., Pezaros, D. P., & Toka, L. (2020). Transition to SDN is HARMLESS: Hybrid Architecture for Migrating Legacy Ethernet Switches to SDN. IEEE/ACM Transactions on Networking, 28(1), 275-288. doi:10.1109/tnet.2019.2958762Dawadi, B. R., Rawat, D. B., Joshi, S. R., & Manzoni, P. (2020). Legacy Network Integration with SDN-IP Implementation towards a Multi-Domain SoDIP6 Network Environment. Electronics, 9(9), 1454. doi:10.3390/electronics9091454HongDK MaY BanerjeeS MaoZM.Incremental deployment of SDN in hybrid enterprise and ISP networks. In: Proceedings of the Symposium on SDN Research. 2016:1‐7.Karakus, M., & Durresi, A. (2018). Economic Viability of Software Defined Networking (SDN). Computer Networks, 135, 81-95. doi:10.1016/j.comnet.2018.02.015Rizvi, S. N., Raumer, D., Wohlfart, F., & Carle, G. (2015). Towards carrier grade SDNs. Computer Networks, 92, 218-226. doi:10.1016/j.comnet.2015.09.029Sezer, S., Scott-Hayward, S., Chouhan, P., Fraser, B., Lake, D., Finnegan, J., … Rao, N. (2013). Are we ready for SDN? Implementation challenges for software-defined networks. IEEE Communications Magazine, 51(7), 36-43. doi:10.1109/mcom.2013.6553676Raza, M. H., Sivakumar, S. C., Nafarieh, A., & Robertson, B. (2014). A Comparison of Software Defined Network (SDN) Implementation Strategies. Procedia Computer Science, 32, 1050-1055. doi:10.1016/j.procs.2014.05.532Goransson, P., & Black, C. (2014). SDN in the Data Center. Software Defined Networks, 145-167. doi:10.1016/b978-0-12-416675-2.00007-3AT & T.Introducing the “User Defined Network Cloud”.https://about.att.com/newsroom/introducing_the_user_defined_network_cloud.html. Published 2014. Accessed August 12 2018.CsikorL TokaL SzalayM PongráczG PezarosDP RétváriG.HARMLESS: Cost‐effective transitioning to SDN for small enterprises. In: 2018 IFIP Networking Conference (IFIP Networking) and Workshops. ; 2018:1–9.ON.LAB.Driving SDN Adoption in Service Provider Networks.2014.http://onosproject.org/wp-content/uploads/2014/11/Whitepaper-Service-Provider-SDN-final.pdfBabikerH NikolovaI ChittimaneniKKK.Deploying IPv6 in the Google Enterprise Network. Lessons learned. In:LISA'11 Proceedings of the 25th International Conference on Large Installation System Administration 2011:10.ParkHW HwangISLS LeeJR.Study on the sustainable migration to software defined network for nation‐wide R&E network.Proc—201610th Int Conf Innov Mob Internet Serv Ubiquitous Comput IMIS2016.2016:392‐396.https://doi.org/10.1109/IMIS.2016.117CariaM JukanA HoffmannM.A performance study of network migration to SDN‐enabled traffic engineering. In:2013 IEEE Global Communications Conference (GLOBECOM); 2013:1391‐1396.Sandhya, Sinha, Y., & Haribabu, K. (2017). A survey: Hybrid SDN. Journal of Network and Computer Applications, 100, 35-55. doi:10.1016/j.jnca.2017.10.003LENCSE, G., & KADOBAYASHI, Y. (2019). Comprehensive Survey of IPv6 Transition Technologies: A Subjective Classification for Security Analysis. IEICE Transactions on Communications, E102.B(10), 2021-2035. doi:10.1587/transcom.2018ebr0002NIST.Technical and Economic Assessment of Internet Protocol Verson 6 9IPv6.2006.https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=912231NIST.IPv6 Economic Impact Assessment. NY;2005.https://www.nist.gov/system/files/documents/director/planning/report05-2.pdfDasT CariaM JukanA HoffmannM.A Techno‐economic Analysis of Network Migration to Software‐Defined Networking.2013.http://arxiv.org/abs/1310.0216Das, T., Drogon, M., Jukan, A., & Hoffmann, M. (2014). Study of Network Migration to New Technologies Using Agent-Based Modeling Techniques. Journal of Network and Systems Management, 23(4), 920-949. doi:10.1007/s10922-014-9327-3Yuan, T., Huang, X., Ma, M., & Zhang, P. (2017). Migration to software-defined networks: The customers’ view. China Communications, 14(10), 1-11. doi:10.1109/cc.2017.8107628TürkS LiuY RadekeR LehnertR.Network migration optimization using genetic algorithms. In: Meeting of the European Network of Universities and Companies in Information and Communication Engineering. 2012:112–123.Türk, S. (2014). Network migration optimization using meta-heuristics. AEU - International Journal of Electronics and Communications, 68(7), 584-586. doi:10.1016/j.aeue.2014.04.005TürkS RadekeR LehnertR.Network migration using ant colony optimization. In:2010 9th Conference of Telecommunication Media and Internet; 2010:1–6.TurkS LiuH RadekeR LehnertR.Improving network migration optimization utilizing memetic algorithms. In: Global Information Infrastructure Symposium—GIIS 2013. 2013:1‐8.https://doi.org/10.1109/GIIS.2013.6684345ShayaniD Mas MachucaC JagerM GladischA.Cost analysis of the service migration problem between communication platforms. In: NOMS 2008–2008 IEEE Network Operations and Management Symposium. 2008:734‐737.https://doi.org/10.1109/NOMS.2008.4575201Shayani, D., Mas Machuca, C., & Jager, M. (2010). A techno-economic approach to telecommunications: the case of service migration. IEEE Transactions on Network and Service Management, 7(2), 96-106. doi:10.1109/tnsm.2010.06.i8p0297Naudts, B., Kind, M., Verbrugge, S., Colle, D., & Pickavet, M. (2015). How can a mobile service provider reduce costs with software-defined networking? International Journal of Network Management, 26(1), 56-72. doi:10.1002/nem.1919Dawadi, B. R., Rawat, D. B., & Joshi, S. R. (2019). Evolutionary Dynamics of Service Provider Legacy Network Migration to Software Defined IPv6 Network. Advances in Intelligent Systems and Computing, 245-257. doi:10.1007/978-3-030-19861-9_24BezrukVM ChebotarovaD V KaliuzhniyNM QiangG YuZ.Optimization and mathematical modeling of communication networks.Monogr—Open Electron Arch Kharkov Natl Univ Radio Electron.2019.http://openarchive.nure.ua/handle/document/10121Omantek. Open‐AudIT: Device Information Management System.https://www.open-audit.org/about.phpNet. Inventory Advisor.Network Inventory Software.https://www.network-inventory-advisor.com/. Accessed December 3 2019.OCS‐Inventory. OCSING: Open Inventory Next Generation.https://ocsinventory-ng.org/?lang=en. Accessed December 3 2019.Group MW. Migration Use Cases and Methods Migration Working Group Open Networking Foundation Use Cases and Migration Methods 2.www.opennetworking.orgSohn, S. Y., & Kim, Y. (2011). Economic Evaluation Model for International Standardization of Correlated Technologies. IEEE Transactions on Engineering Management, 58(2), 189-198. doi:10.1109/tem.2010.2058853ONF TS‐006.OpenFlow 1.3 Switch Specification.2012.https://www.opennetworking.org/wp-content/uploads/2014/10/openflow-spec-v1.3.0.pdfMahlooM MontiP ChenJ WosinskaL.Cost modeling of backhaul for mobile networks. In: 2014 IEEE International Conference on Communications Workshops (ICC). 2014:397–402.https://doi.org/10.1109/ICCW.2014.6881230DawadiBR RawatDB JoshiSR KeitschMM.Joint cost estimation approach for service provider legacy network migration to unified software defined IPv6 network. In: Proceedings—4th IEEE International Conference on Collaboration and Internet Computing CIC 2018.2018.https://doi.org/10.1109/CIC.2018.00056FengT BiJ.OpenRouteFlow: Enable legacy router as a software‐defined routing service for hybrid SDN. In: 2015 24th International Conference on Computer Communication and Networks (ICCCN).2015:1–8.MachucaCM EberspaecherJ JägerM GladischA.Service migration cost modeling. In: 2007 ITG Symposium on Photonic Networks. ; 2007:1–5.Poularakis, K., Iosifidis, G., Smaragdakis, G., & Tassiulas, L. (2019). Optimizing Gradual SDN Upgrades in ISP Networks. IEEE/ACM Transactions on Networking, 27(1), 288-301. doi:10.1109/tnet.2018.2890248Galán-Jiménez, J. (2017). Legacy IP-upgraded SDN nodes tradeoff in energy-efficient hybrid IP/SDN networks. Computer Communications, 114, 106-123. doi:10.1016/j.comcom.2017.10.010Vizarreta, P., Trivedi, K., Helvik, B., Heegaard, P., Blenk, A., Kellerer, W., & Mas Machuca, C. (2018). Assessing the Maturity of SDN Controllers With Software Reliability Growth Models. IEEE Transactions on Network and Service Management, 15(3), 1090-1104. doi:10.1109/tnsm.2018.2848105Salsano, S., Ventre, P. L., Lombardo, F., Siracusano, G., Gerola, M., Salvadori, E., … Prete, L. (2016). Hybrid IP/SDN Networking: Open Implementation and Experiment Management Tools. IEEE Transactions on Network and Service Management, 13(1), 138-153. doi:10.1109/tnsm.2015.2507622DasT GurusamyM.Resilient Controller Placement in Hybrid SDN/Legacy Networks. In: 2018 IEEE Global Communications Conference (GLOBECOM). 2018:1–7.DasT GurusamyM.INCEPT: INcremental ControllEr PlacemenT in software defined networks. In: 2018 27th International Conference on Computer Communication and Networks (ICCCN). 2018:1–6

ANCHOR: logically-centralized security for Software-Defined Networks

While the centralization of SDN brought advantages such as a faster pace of innovation, it also disrupted some of the natural defenses of traditional architectures against different threats. The literature on SDN has mostly been concerned with the functional side, despite some specific works concerning non-functional properties like 'security' or 'dependability'. Though addressing the latter in an ad-hoc, piecemeal way, may work, it will most likely lead to efficiency and effectiveness problems. We claim that the enforcement of non-functional properties as a pillar of SDN robustness calls for a systemic approach. As a general concept, we propose ANCHOR, a subsystem architecture that promotes the logical centralization of non-functional properties. To show the effectiveness of the concept, we focus on 'security' in this paper: we identify the current security gaps in SDNs and we populate the architecture middleware with the appropriate security mechanisms, in a global and consistent manner. Essential security mechanisms provided by anchor include reliable entropy and resilient pseudo-random generators, and protocols for secure registration and association of SDN devices. We claim and justify in the paper that centralizing such mechanisms is key for their effectiveness, by allowing us to: define and enforce global policies for those properties; reduce the complexity of controllers and forwarding devices; ensure higher levels of robustness for critical services; foster interoperability of the non-functional property enforcement mechanisms; and promote the security and resilience of the architecture itself. We discuss design and implementation aspects, and we prove and evaluate our algorithms and mechanisms, including the formalisation of the main protocols and the verification of their core security properties using the Tamarin prover.Comment: 42 pages, 4 figures, 3 tables, 5 algorithms, 139 reference

Software defined wireless sensor networks application opportunities for efficient network management : a survey

Wireless Sensor Networks (WSNs) are commonly used information technologies of modern networking and computing platforms. Today's network computing applications are faced with a high demand of powerful network functionalities. Functional network reach is central to customer satisfaction such as in mobile networks and cloud computing environments. However, efficient management of WSNs remains a challenge, due to problems supplemental to them. Recent technology shift proposes Software Defined Networking (SDN) for improving computing networks. This review paper highlights application challenges faced by WSNs for monitored environments and those faced by the proposed approaches, as well as opportunities that can be realized on applications of WSNs using SDN. We also highlight Implementation considerations by focusing on critical aspects that should not be disregarded when attempting to improve network functionalities. We then propose a strategy for Software Defined Wireless Sensor Network (SDWSN) as an effort for application improvement in monitored environments.The National Research Foundation (NRF) of South Africa (grant number: RDYR160404161474 and IFR160118156967).http://www.elsevier.com/locate/compeleceng2019-02-01hj2018Electrical, Electronic and Computer Engineerin

Enabling virtual radio functions on software defined radio for future wireless networks

Today's wired networks have become highly flexible, thanks to the fact that an increasing number of functionalities are realized by software rather than dedicated hardware. This trend is still in its early stages for wireless networks, but it has the potential to improve the network's flexibility and resource utilization regarding both the abundant computational resources and the scarce radio spectrum resources. In this work we provide an overview of the enabling technologies for network reconfiguration, such as Network Function Virtualization, Software Defined Networking, and Software Defined Radio. We review frequently used terminology such as softwarization, virtualization, and orchestration, and how these concepts apply to wireless networks. We introduce the concept of Virtual Radio Function, and illustrate how softwarized/virtualized radio functions can be placed and initialized at runtime, allowing radio access technologies and spectrum allocation schemes to be formed dynamically. Finally we focus on embedded Software-Defined Radio as an end device, and illustrate how to realize the placement, initialization and configuration of virtual radio functions on such kind of devices

SDN as Active Measurement Infrastructure

Active measurements are integral to the operation and management of networks, and invaluable to supporting empirical network research. Unfortunately, it is often cost-prohibitive and logistically difficult to widely deploy measurement nodes, especially in the core. In this work, we consider the feasibility of tightly integrating measurement within the infrastructure by using Software Defined Networks (SDNs). We introduce "SDN as Active Measurement Infrastructure" (SAAMI) to enable measurements to originate from any location where SDN is deployed, removing the need for dedicated measurement nodes and increasing vantage point diversity. We implement ping and traceroute using SAAMI, as well as a proof-of-concept custom measurement protocol to demonstrate the power and ease of SAAMI's open framework. Via a large-scale measurement campaign using SDN switches as vantage points, we show that SAAMI is accurate, scalable, and extensible

Software-Defined Cloud Computing: Architectural Elements and Open Challenges

The variety of existing cloud services creates a challenge for service providers to enforce reasonable Software Level Agreements (SLA) stating the Quality of Service (QoS) and penalties in case QoS is not achieved. To avoid such penalties at the same time that the infrastructure operates with minimum energy and resource wastage, constant monitoring and adaptation of the infrastructure is needed. We refer to Software-Defined Cloud Computing, or simply Software-Defined Clouds (SDC), as an approach for automating the process of optimal cloud configuration by extending virtualization concept to all resources in a data center. An SDC enables easy reconfiguration and adaptation of physical resources in a cloud infrastructure, to better accommodate the demand on QoS through a software that can describe and manage various aspects comprising the cloud environment. In this paper, we present an architecture for SDCs on data centers with emphasis on mobile cloud applications. We present an evaluation, showcasing the potential of SDC in two use cases-QoS-aware bandwidth allocation and bandwidth-aware, energy-efficient VM placement-and discuss the research challenges and opportunities in this emerging area.Comment: Keynote Paper, 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI 2014), September 24-27, 2014, Delhi, Indi