SDN aims to facilitate the management of increasingly complex, dynamic network environments and optimize the use of the resources available therein with minimal operator intervention. To this end, SDN controllers maintain a global view of the network topology and its state. However, the extraction of information about network flows and other network metrics remains a non-trivial challenge. Network applications exhibit a wide range of properties, posing diverse, often conflicting, demands towards the network. As these requirements are typically not known, controllers must rely on error-prone heuristics to extract them. In this work, we develop a framework which allows applications deployed in an SDN environment to explicitly express their requirements to the network. Conversely, it allows network controllers to deploy policies on end-hosts and to supply applications with information about network paths, salient servers and other relevant metrics. The proposed approach opens the door for fine grained, application-aware resource optimization strategies in SDNs

The NEAT System offers an enhanced API for applications that disentangles them from the actual transport protocol being used. The system also enables applications to communicate their service requirements to the transport system in a generic, transport-protocol independent way. Moreover, the architecture of the NEAT System promotes the evolution of new transport services. Work Package 3 (WP3) enhances and extends the core parts of the NEAT Transport. Efforts have been devoted to developing transport-protocol mechanisms that enable a wider spectrum of NEAT Transport Services, and that assist the NEAT System in facilitating several of the commercial use cases. Work has also started on the development of optimal transport-selection mechanisms; mechanisms that enable for the NEAT System to make optimal transport selections on the basis of application requirements and network measurements. Lastly, another research activity has been initiated on how to use SDN to signal application requirements to routers, switches, and similar network elements. This document provides an initial report on all these WP3 activities—both on completed and on near-termplanned work.

This paper presents a novel concept for enhanced mobile broadband (eMBB) communication using millimeter-wave radio technologies enhanced by mobile edge computing to support a new class of applications requiring low latency and high data rates at the same time. The concept developed in the joint European/Japanese collaboration project 5G-MiEdge [1] builds on meshed backhaul topologies using millimeter wave links with beam forming capabilities and smart routing units for dynamic route, link and power management to be orchestrated by SDN. It is shown that dynamic changes in the topology at run time can be realized without experiencing losses in latency or throughput.

Next generation, i.e., fifth generation (5G), cellular networks will provide a significant higher capacity per area to support the ever-increasing traffic demands. In order to achieve that, many small cells need to be deployed that are connected using a combination of optical fiber links and millimeter-wave (mmWave) backhaul architecture to forward heterogeneous traffic over mesh topologies. In this paper, we present a general optimization framework for the design of policies that optimally solve the problem of where to associate a user, over which links to route its traffic towards which mesh gateway, and which base stations and backhaul links to switch off in order to minimize the energy cost for the network operator and still satisfy the user demands. We develop an optimal policy based on mixed integer linear programming (MILP) which considers different user distribution and traffic demands over multiple time periods. We develop also a fast iterative two-phase solution heuristic, which associates users and calculates backhaul routes to maximize energy savings. Our strategies optimize the backhaul network configuration at each timeslot based on the current demands and user locations. We discuss the application of our policies to backhaul management of mmWave cellular networks in light of current trend of network softwarization (Software-Defined Networking, SDN). Finally, we present extensive numerical simulations of our proposed policies, which show how the algorithms can efficiently trade-off energy consumption with required capacity, while satisfying flow demand requirements.

Current technological advances have caused an exponential growth of the number of mobile Internet-connected devices, along with their respective traffic demands. To cope with this increase of traffic demands, fifth generation (5G) network architectures will need to provide multi-gigabit capacity at the access base stations (BSs), through the deployment of ultra-dense small cells (SCs) operating with millimeter-wave (mmWave) frequencies, e.g. 60 GHz. To connect the BSs to the core network, a robust and high capacity backhaul infrastructure is required. As it is unfeasible to connect all the SCs through optical fiber links, a solution for the future 5G backhaul relies on the usage of mmWave frequencies to interconnect the SCs, forming multi-hop wireless mesh topologies. In this thesis, we explore the application of the Software-defined Networking (SDN) paradigm for the management of a SC wireless backhaul. With SDN, the data and control planes are separated and the network management is done by a centralized controller entity that has a global network view. To that end, we provide multiple contributions. Firstly, we provide an SDN-based architecture to manage SC backhaul networks, which include an out-of-band Long Term Evolution (LTE) control channel and where we consider aspects such as energy efficiency, resiliency and flexible backhaul operation. Secondly, we demonstrate the benefit of the wireless backhaul configuration using the SDN controller, which can be used to improve the wireless resource allocation and provide resiliency mechanisms in the network. Finally, we investigate how a SC mesh backhaul can be optimally reconfigured between different topologies, focusing on minimizing the network disruption during the reconfiguration.

The increase of mobile devices and services over the last decade has led to unprecedented mobile traffic growth. To cope with the increasing demands, fifth generation (5G) network architectures have been designed to provide the required capacity using a large number of small cells (SCs). However, a dense deployment of SCs requires a robust and scalable backhaul to transport the access traffic towards the Internet. In this thesis, we explore the application of the Software-defined Networking (SDN) paradigm for the management of a wireless backhaul. With SDN, the data and control planes are separated and the network is managed by a centralized entity. To that end, we provide multiple contributions that focus on achieving resilient and reconfigurable wireless backhaul networks. Firstly, we propose an SDN-based architecture to manage the wireless backhaul. Our architecture is integrated in practical testbed environments, where we use an SDN controller to configure the forwarding plane and wireless backhaul links. Secondly, we evaluate SDN-based resiliency in the wireless backhaul. We achieve that by implementing fast-failover resiliency with OpenFlow group tables and by using the bidirectional-forwarding detection protocol (BFD) to monitor the state of the backhaul links. Finally, we develop algorithms that calculate the necessary reconfiguration operations to transition between different wireless backhaul topologies, while minimizing the impact on existing user traffic. We consider that the backhaul nodes can be powered on/off and are equipped with steerable antennas that can be aligned to form links with different neighbors. Our optimization problems are modeled as mixed integer linear programs (MILP) that are optimally solved using exact mathematical programming methods. In addition, we develop greedy-based heuristic algorithms that solve the same problems and obtain good quality solutions in short time.

Software-Defined Networking (SDN) has led to a paradigm shift in the way how networks are managed and operated. In SDN environments the data plane forwarding rules are managed by logically centralized controllers operating on global view of the network. Today, SDN controllers typically posses little insight about the requirements of the applications executed on the end-hosts. Consequently, they rely on heuristics to implement traffic engineering or QoS support. In this work, we propose a framework for application-awareness in SDN environments where the end-hosts provide a generic interface for the SDN controllers to interact with. As a result, SDN controllers may enhance the end-host’s view of the attached network and deploy policies into the edge of the network. Further, controllers may obtain information about the specific requirements of the deployed applications. Our demonstration extends the OpenDaylight SDN controller to enable it to interact with end-hosts running a novel networking stack called NEAT. We demonstrate a scenario in which the controller distributes policies and path information to manage bulk and low-latency flows. 

Future 5G mobile networks will require increased backhaul (BH) capacity to connect a massive amount of high capacity small cells (SCs) to the network. Because having an optical connection to each SC might be infeasible, mmWave-based (e.g. 60 GHz) BH links are an interesting alternative due to their large available bandwidth. To cope with the increased path loss, mmWave links require directional antennas that should be able to direct their beams to different neighbors, to dynamically change the BH topology, in case new nodes are powered on/off or the traffic demand has changed. Such BH adaptation needs to be orchestrated to minimize the impact on existing traffic.This paper develops a Software-defined networking-based framework that guides the optimal reconfiguration of mesh BH networks composed by mmWave links, where antennas need to be mechanically aligned.By modelling the problem as a Mixed Integer Linear Program (MILP), its solution returns the optimal ordering of events necessary to transition between two BH network configurations. The model creates backup paths whenever it is possible, while minimizing the packet loss of ongoing flows. A numerical evaluation with different topologies and traffic demands shows that increasing the number of BH interfaces per SC from 2 to 4 can decrease the total loss by more than 50%. Moreover, when increasing the total reconfiguration time, additional backup paths can be created, consequently reducing the reconfiguration impact on existing traffic.

In order to increase the capacity of next generation mobile networks, network densification is a key aspect to provide better coverage and increased data rates to end users. Network operators are thinking to deploy wireless backhaul solutions to cut down cabling costs for connecting the small cell nodes. Consequently, the next generation mobile network architecture may contain a massive amount of small cells that are connected through wireless backhaul links, forming mesh or tree structures towards the core network, under the umbrella coverage of eNodeB type macro cells. In this paper, we use a Software-Defined Networking (SDN) based architecture for the operation and management of such small cell backhaul networks. By extending OpenFlow, the SDN controller is able to reconfigure not only the routing, but also the wireless backhaul configuration, such as channel assignment to backhaul links. We demonstrate the effectiveness of our approach by using testbed measurements and show that, when using our SDN-based reconfiguration, the network downtime for existing traffic due to channel re-assignment is significantly reduced, when comparing to a distributed routing based approach. Moreover, by using SDN based fast-failover techniques, we can instantaneously redirect traffic to other neighbors when links fail or neighbors are powered down, without the need for controller interaction.

Future mobile data traffic predictions expect a significant increase in user data traffic, requiring new forms of mobile network infrastructures. Fifth generation (5G) communication standards propose the densification of small cell access base stations (BSs) in order to provide multigigabit and low latency connectivity. This densification requires a high capacity backhaul network. Using optical links to connect all the small cells is economically not feasible for large scale radio access networks where multiple BSs are deployed. A wireless backhaul formed by a mesh of millimeter-wave (mmWave) links is an attractive mobile backhaul solution, as flexible wireless (multihop) paths can be formed to interconnect all the access BSs. Moreover, a wireless backhaul allows the dynamic reconfiguration of the backhaul topology to match varying traffic demands or adaptively power on/off small cells for green backhaul operation. However, conducting and precisely controlling reconfiguration experiments over real mmWave multihop networks is a challenging task. In this paper, we develop a Software-Defined Networking (SDN) based approach to enable such a dynamic backhaul reconfiguration and use real-world mmWave equipment to setup a SDN-enabled mmWave testbed to conduct various reconfiguration experiments. In our approach, the SDN control plane is not only responsible for configuring the forwarding plane but also for the link configuration, antenna alignment, and adaptive mesh node power on/off operations. We implement the SDN-based reconfiguration operations in a testbed with four nodes, each equipped with multiple mmWave interfaces that can be mechanically steered to connect to different neighbors. We evaluate the impact of various reconfiguration operations on existing user traffic using a set of extensive testbed measurements. Moreover, we measure the impact of the channel assignment on existing traffic, showing that a setup with an optimal channel assignment between the mesh links can result in a 44% throughput increase, when compared to a suboptimal configuration.

As a solution to cope with the increase of wireless network traffic for future 5G networks, the IEEE 802.11ad standard enables multi-gigabit connectivity within the 60 GHz spectrum. Since these networks typically have low range, a vast number of small cells is required to form a wireless backhaul that can be easily affected by temporary failures due to blockage/interference. Software-defined Networking (SDN) is a paradigm that allows the centralization of the control plane management, which can be applied to mmWave wireless backhaul networks. Using SDN enables the possibility of having resilience mechanisms in the network, such as Fast-Failover (FF) group tables in the OpenFlow (OF) protocol. In this paper, we analyse resilient forwarding configurations upon temporary link failures. We perform our evaluation on a 4 small cell testbed with multiple IEEE 802.11ad interfaces, showing how OF-based resiliency can be applied, through FF and the Bidirectional-Forwarding Detection (BFD) protocol. Our results show how BFD can be tuned to improve the link state monitoring, and how a local reactive failover mechanism can benefit ongoing traffic in small cell meshed backhaul networks.

Five-G heterogeneous network overlaid by millimeter-wave (mmWave) access employs mmWave meshed backhauling as a promising cost-efficient backhaul architecture. Due to the nature of mobile traffic distribution in practice which is both time-variant and spatially non-uniform, dynamic construction of mmWave meshed backhaul is a prerequisite to support the varying traffic distribution. Focusing on such scenario of outdoor dynamic crowd (ODC), this paper proposes a novel method to control mmWave meshed backhaul for efficient operation of mmWave overlay 5G HetNet through Software-Defined Network (SDN) technology. Our algorithm is featured by two functionalities, i.e., backhauling route multiplexing for overloaded mmWave small cell base stations (SC-BSS) and mmWave SC-BSS' ON/OFF status switching for underloaded spot. In this paper, the effectiveness of the proposed meshed network is confirmed by both numerical analyses and experimental results. Simulations are conducted over a practical user distribution modeled from measured data in realistic environments. Numerical results show that the proposed algorithm can cope with the locally intensive traffic and reduce energy consumption. Furthermore, a WiGig (Wireless Gigabit Alliance certified) device based testbed is developed for Proof-of-Concept (PoC) and preliminary measurement results confirm the proposed dynamic formation of the meshed network's efficiency.