SODALITE: SDN wireless backhauling for dense 4G/5G Small Cell networks

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Dense deployments of Small Cells are key to fulfill the capacity requirements of future 5G networks. However, two roadblocks to the adoption of Small Cells are i) the limited availability and the cost of sites with wired backhaul resources, and ii) the complexity to manage a dense deployment of wireless backhaul nodes. Towards these challenges we propose SODALITE, a novel system that applies Software Defined Networking (SDN) to a wireless backhaul network. We present how SODALITE can be integrated to 3GPP’s 4G and 5G architectures, and show the feasibility of SODALITE through LTE network testbed experiments. We substantiate the scalability of SODALITE through stochastic studies using real-life traffic traces from an LTE network and discuss the effects of cell densification and 5G system architecture on these studies. Further, a reliable backhauling solution for wireless links is introduced in SODALITE through SDN-enabled mechanisms that are capable of reconfiguring the data plane upon a link failure detection. Its reliability is shown through experiments on a LTE network testbed, and studied thoroughly via rigorous simulations and network emulator evaluations. As a result, we claim that SODALITE is a promising carrier-grade system to manage a wireless Small Cell backhaul.Postprint (author's final draft

Joint routing and resource allocation for wireless backhauling of small cell networks

The future communication networks are destined to support an increasingly large amount of data traffic, and for that reason, efficient mechanisms to manage them are necessary. Based on a backhaul network, and starting from specific scenarios, we develop methods to jointly optimize the routing parameters and resources of this network. We relate this optimization with the Software Defined Networks and network virtualization concepts, which allow us to have an overall vision of the network, and lead us to study its decomposition. To do this, we use convex optimization techniques, which have very efficient resolution mechanisms, and help us to obtain tools for interpreting the obtained results and perform analysis on the network parameters. The achieved results show a great improvement in relation to the non-optimized case in terms of carried traffic, which is an assessment we make in the final economic analysis.Las redes de comunicaciones del futuro están destinadas a soportar una cantidad de tráfico de datos cada vez más elevada, y por eso son necesarios mecanismos eficientes para gestionarlas. Basándonos en una red de backhaul y partiendo de escenarios concretos, desarrollamos métodos para optimizar conjuntamente los parámetros de enrutamiento y los recursos de esta red. Esta optimización la ligamos con los conceptos de Software Defined Networksk y de network virtualization, que nos permiten tener una visión general de la red, y nos conducen a estudiar su descomposición. Esto lo hacemos usando técnicas de optimización convexa, que tiene mecanismos de resolución muy eficientes, y nos ayuda a obtener herramientas para interpretar los resultados obtenidos y hacer análisis de los parámetros de la red. Los resultados conseguidos muestran una gran mejora con relación al caso no optimizado en términos de tráfico transportado, valoración que recogemos en un análisis económico final.Les xarxes de comunicacions del futur estan destinades a suportar una quantitat de trànsit de dades cada cop més elevada, i per això són necessaris mecanismes eficients per a gestionar-les. Basant-nos en una xarxa de backhaul i partint d?escenaris concrets, desenvolupem mètodes per a optimitzar conjuntament els paràmetres d?encaminament i els recursos d?aquesta xarxa. Aquesta optimització la lliguem amb els conceptes de Software Defined Network i de network virtualization, que ens permeten tenir una visió general de la xarxa, i ens condueixen a estudiar-ne la seva descomposició. Tot això ho fem utilitzant tècniques d?optimització convexa, que té mecanismes de resolució molt eficients, i ens ajuda a obtenir eines per a interpretar els resultats obtinguts i fer anàlisis dels punts forts i febles de la xarxa. Els resultats aconseguits mostren una gran millora respecte el cas no optimitzat en termes de trànsit transportat, valoració que recollim en una anàlisi econòmica final

On the benefits of wireless SDN in networks of constrained edge devices

In this paper we study the benefits of applying Software Defined Networking (SDN) to control forwarding in a network of constrained wireless edge devices. The proposed architecture is applicable to dense Small Cell deployments featuring wireless backhauling and edge computing capabilities, or to wirelessly connected sensor nodes following the fog computing paradigm. The paper introduces a novel path forwarding policy based on SDN, and presents an experimental evaluation demonstrating the benefits of the proposed policy to mitigate external interference, achieve flow balancing, and cope with CPU constrained devices.Peer ReviewedPostprint (published version

On the benefits of wireless SDN in networks of constrained edge devices

In this paper we study the benefits of applying Software Defined Networking (SDN) to control forwarding in a network of constrained wireless edge devices. The proposed architecture is applicable to dense Small Cell deployments featuring wireless backhauling and edge computing capabilities, or to wirelessly connected sensor nodes following the fog computing paradigm. The paper introduces a novel path forwarding policy based on SDN, and presents an experimental evaluation demonstrating the benefits of the proposed policy to mitigate external interference, achieve flow balancing, and cope with CPU constrained devices.Peer Reviewe