Will SDN be part of 5G?

For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure

Software Defined Applications in Cellular and Optical Networks

abstract: Small wireless cells have the potential to overcome bottlenecks in wireless access through the sharing of spectrum resources. A novel access backhaul network architecture based on a Smart Gateway (Sm-GW) between the small cell base stations, e.g., LTE eNBs, and the conventional backhaul gateways, e.g., LTE Servicing/Packet Gateways (S/P-GWs) has been introduced to address the bottleneck. The Sm-GW flexibly schedules uplink transmissions for the eNBs. Based on software defined networking (SDN) a management mechanism that allows multiple operator to flexibly inter-operate via multiple Sm-GWs with a multitude of small cells has been proposed. This dissertation also comprehensively survey the studies that examine the SDN paradigm in optical networks. Along with the PHY functional split improvements, the performance of Distributed Converged Cable Access Platform (DCCAP) in the cable architectures especially for the Remote-PHY and Remote-MACPHY nodes has been evaluated. In the PHY functional split, in addition to the re-use of infrastructure with a common FFT module for multiple technologies, a novel cross functional split interaction to cache the repetitive QAM symbols across time at the remote node to reduce the transmission rate requirement of the fronthaul link has been proposed.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

Towards cognitive in-operation network planning

Next-generation internet services such as live TV and video on demand require high bandwidth and ultra-low latency. The ever-increasing volume, dynamicity and stringent requirements of these services’ demands are generating new challenges to nowadays telecom networks. To decrease expenses, service-layer content providers are delivering their content near the end users, thus allowing a low latency and tailored content delivery. As a consequence of this, unseen metro and even core traffic dynamicity is arising with changes in the volume and direction of the traffic along the day. A tremendous effort to efficiently manage networks is currently ongoing towards the realisation of 5G networks. This translates in looking for network architectures supporting dynamic resource allocation, fulfilling strict service requirements and minimising the total cost of ownership (TCO). In this regard, in-operation network planning was recently proven to successfully support various network reconfiguration use cases in prospective scenarios. Nevertheless, additional research to extend in-operation planning capabilities from typical reactive optimization schemes to proactive and predictive schemes based on the analysis of network monitoring data is required. A hot topic raising increasing attention is cognitive networking, where an elevated knowledge about the network could be obtained as a result of introducing data analytics in the telecom operator’s infrastructure. By using predictive knowledge about the network traffic, in-operation network planning mechanisms could be enhanced to efficiently adapt the network by means of future traffic prediction, thus achieving cognitive in-operation network planning. In this thesis, we focus on studying mechanisms to enable cognitive in-operation network planning in core networks. In particular, we focus on dynamically reconfiguring virtual network topologies (VNT) at the MPLS layer, covering a number of detailed objectives. First, we start studying mechanisms to allow network traffic flow modelling, from monitoring and data transformation to the estimation of predictive traffic model based on this data. By means of these traffic models, then we tackle a cognitive approach to periodically adapt the core VNT to current and future traffic, using predicted traffic matrices based on origin-destination (OD) predictive models. This optimization approach, named VENTURE, is efficiently solved using dedicated heuristic algorithms and its feasibility is demonstrated in an experimental in-operation network planning environment. Finally, we extend VENTURE to consider core flows dynamicity as a result of metro flows re-routing, which represents a meaningful dynamic traffic scenario. This extension, which entails enhancements to coordinate metro and core network controllers with the aim of allowing fast adaption of core OD traffic models, is evaluated and validated in terms of traffic models accuracy and experimental feasibility.Els serveis d’internet de nova generació tals com la televisió en viu o el vídeo sota demanda requereixen d’un gran ample de banda i d’ultra-baixa latència. L’increment continu del volum, dinamicitat i requeriments d’aquests serveis està generant nous reptes pels teleoperadors de xarxa. Per reduir costs, els proveïdors de contingut estan disposant aquests més a prop dels usuaris finals, aconseguint així una entrega de contingut feta a mida. Conseqüentment, estem presenciant una dinamicitat mai vista en el tràfic de xarxes de metro amb canvis en la direcció i el volum del tràfic al llarg del dia. Actualment, s’està duent a terme un gran esforç cap a la realització de xarxes 5G. Aquest esforç es tradueix en cercar noves arquitectures de xarxa que suportin l’assignació dinàmica de recursos, complint requeriments de servei estrictes i minimitzant el cost total de la propietat. En aquest sentit, recentment s’ha demostrat com l’aplicació de “in-operation network planning” permet exitosament suportar diversos casos d’ús de reconfiguració de xarxa en escenaris prospectius. No obstant, és necessari dur a terme més recerca per tal d’estendre “in-operation network planning” des d’un esquema reactiu d’optimització cap a un nou esquema proactiu basat en l’analítica de dades provinents del monitoritzat de la xarxa. El concepte de xarxes cognitives es també troba al centre d’atenció, on un elevat coneixement de la xarxa s’obtindria com a resultat d’introduir analítica de dades en la infraestructura del teleoperador. Mitjançant un coneixement predictiu sobre el tràfic de xarxa, els mecanismes de in-operation network planning es podrien millorar per adaptar la xarxa eficientment basant-se en predicció de tràfic, assolint així el que anomenem com a “cognitive in-operation network Planning”. En aquesta tesi ens centrem en l’estudi de mecanismes que permetin establir “el cognitive in-operation network Planning” en xarxes de core. En particular, ens centrem en reconfigurar dinàmicament topologies de xarxa virtual (VNT) a la capa MPLS, cobrint una sèrie d’objectius detallats. Primer comencem estudiant mecanismes pel modelat de fluxos de tràfic de xarxa, des del seu monitoritzat i transformació fins a l’estimació de models predictius de tràfic. Posteriorment, i mitjançant aquests models predictius, tractem un esquema cognitiu per adaptar periòdicament la VNT utilitzant matrius de tràfic basades en predicció de parells origen-destí (OD). Aquesta optimització, anomenada VENTURE, és resolta eficientment fent servir heurístiques dedicades i és posteriorment avaluada sota escenaris de tràfic de xarxa dinàmics. A continuació, estenem VENTURE considerant la dinamicitat dels fluxos de tràfic de xarxes de metro, el qual representa un escenari rellevant de dinamicitat de tràfic. Aquesta extensió involucra millores per coordinar els operadors de metro i core amb l’objectiu d’aconseguir una ràpida adaptació de models de tràfic OD. Finalment, proposem dues arquitectures de xarxa necessàries per aplicar els mecanismes anteriors en entorns experimentals, emprant protocols estat-de-l’art com són OpenFlow i IPFIX. La metodologia emprada per avaluar el treball anterior consisteix en una primera avaluació numèrica fent servir un simulador de xarxes íntegrament dissenyat i desenvolupat per a aquesta tesi. Després d’aquesta validació basada en simulació, la factibilitat experimental de les arquitectures de xarxa proposades és avaluada en un entorn de proves distribuït

Towards cognitive in-operation network planning

Next-generation internet services such as live TV and video on demand require high bandwidth and ultra-low latency. The ever-increasing volume, dynamicity and stringent requirements of these services’ demands are generating new challenges to nowadays telecom networks. To decrease expenses, service-layer content providers are delivering their content near the end users, thus allowing a low latency and tailored content delivery. As a consequence of this, unseen metro and even core traffic dynamicity is arising with changes in the volume and direction of the traffic along the day. A tremendous effort to efficiently manage networks is currently ongoing towards the realisation of 5G networks. This translates in looking for network architectures supporting dynamic resource allocation, fulfilling strict service requirements and minimising the total cost of ownership (TCO). In this regard, in-operation network planning was recently proven to successfully support various network reconfiguration use cases in prospective scenarios. Nevertheless, additional research to extend in-operation planning capabilities from typical reactive optimization schemes to proactive and predictive schemes based on the analysis of network monitoring data is required. A hot topic raising increasing attention is cognitive networking, where an elevated knowledge about the network could be obtained as a result of introducing data analytics in the telecom operator’s infrastructure. By using predictive knowledge about the network traffic, in-operation network planning mechanisms could be enhanced to efficiently adapt the network by means of future traffic prediction, thus achieving cognitive in-operation network planning. In this thesis, we focus on studying mechanisms to enable cognitive in-operation network planning in core networks. In particular, we focus on dynamically reconfiguring virtual network topologies (VNT) at the MPLS layer, covering a number of detailed objectives. First, we start studying mechanisms to allow network traffic flow modelling, from monitoring and data transformation to the estimation of predictive traffic model based on this data. By means of these traffic models, then we tackle a cognitive approach to periodically adapt the core VNT to current and future traffic, using predicted traffic matrices based on origin-destination (OD) predictive models. This optimization approach, named VENTURE, is efficiently solved using dedicated heuristic algorithms and its feasibility is demonstrated in an experimental in-operation network planning environment. Finally, we extend VENTURE to consider core flows dynamicity as a result of metro flows re-routing, which represents a meaningful dynamic traffic scenario. This extension, which entails enhancements to coordinate metro and core network controllers with the aim of allowing fast adaption of core OD traffic models, is evaluated and validated in terms of traffic models accuracy and experimental feasibility.Els serveis d’internet de nova generació tals com la televisió en viu o el vídeo sota demanda requereixen d’un gran ample de banda i d’ultra-baixa latència. L’increment continu del volum, dinamicitat i requeriments d’aquests serveis està generant nous reptes pels teleoperadors de xarxa. Per reduir costs, els proveïdors de contingut estan disposant aquests més a prop dels usuaris finals, aconseguint així una entrega de contingut feta a mida. Conseqüentment, estem presenciant una dinamicitat mai vista en el tràfic de xarxes de metro amb canvis en la direcció i el volum del tràfic al llarg del dia. Actualment, s’està duent a terme un gran esforç cap a la realització de xarxes 5G. Aquest esforç es tradueix en cercar noves arquitectures de xarxa que suportin l’assignació dinàmica de recursos, complint requeriments de servei estrictes i minimitzant el cost total de la propietat. En aquest sentit, recentment s’ha demostrat com l’aplicació de “in-operation network planning” permet exitosament suportar diversos casos d’ús de reconfiguració de xarxa en escenaris prospectius. No obstant, és necessari dur a terme més recerca per tal d’estendre “in-operation network planning” des d’un esquema reactiu d’optimització cap a un nou esquema proactiu basat en l’analítica de dades provinents del monitoritzat de la xarxa. El concepte de xarxes cognitives es també troba al centre d’atenció, on un elevat coneixement de la xarxa s’obtindria com a resultat d’introduir analítica de dades en la infraestructura del teleoperador. Mitjançant un coneixement predictiu sobre el tràfic de xarxa, els mecanismes de in-operation network planning es podrien millorar per adaptar la xarxa eficientment basant-se en predicció de tràfic, assolint així el que anomenem com a “cognitive in-operation network Planning”. En aquesta tesi ens centrem en l’estudi de mecanismes que permetin establir “el cognitive in-operation network Planning” en xarxes de core. En particular, ens centrem en reconfigurar dinàmicament topologies de xarxa virtual (VNT) a la capa MPLS, cobrint una sèrie d’objectius detallats. Primer comencem estudiant mecanismes pel modelat de fluxos de tràfic de xarxa, des del seu monitoritzat i transformació fins a l’estimació de models predictius de tràfic. Posteriorment, i mitjançant aquests models predictius, tractem un esquema cognitiu per adaptar periòdicament la VNT utilitzant matrius de tràfic basades en predicció de parells origen-destí (OD). Aquesta optimització, anomenada VENTURE, és resolta eficientment fent servir heurístiques dedicades i és posteriorment avaluada sota escenaris de tràfic de xarxa dinàmics. A continuació, estenem VENTURE considerant la dinamicitat dels fluxos de tràfic de xarxes de metro, el qual representa un escenari rellevant de dinamicitat de tràfic. Aquesta extensió involucra millores per coordinar els operadors de metro i core amb l’objectiu d’aconseguir una ràpida adaptació de models de tràfic OD. Finalment, proposem dues arquitectures de xarxa necessàries per aplicar els mecanismes anteriors en entorns experimentals, emprant protocols estat-de-l’art com són OpenFlow i IPFIX. La metodologia emprada per avaluar el treball anterior consisteix en una primera avaluació numèrica fent servir un simulador de xarxes íntegrament dissenyat i desenvolupat per a aquesta tesi. Després d’aquesta validació basada en simulació, la factibilitat experimental de les arquitectures de xarxa proposades és avaluada en un entorn de proves distribuït.Postprint (published version