While one of the main features of 5G networks is provisioning very high rates with low (or no) variability to cellular users, it has been shown that this turns out to be very ineffective for operators because it leads to an abundance of unused network resources. Yet, reallocating the unused resources to the same users, after providing them with the same constant rate, increases back the variability in data rates. A more efficient way would be to provide different low-variability data rates to the users depending on their channel conditions while trying to bring the wasted resources to the lowest possible extent. To that end, in this paper, two approaches are considered; one with reserved resources for every user and the other where the amount of resources is decided on the fly, depending on their current channel conditions. Then, for each approach, we look at different allocation policies and derive the corresponding maximum achievable constant rate for every user jointly with the level of resource utilization, showing which policy is more beneficial. Further, the performance is evaluated on a real 5G trace using both extensive simulations and real measurements conducted on OpenAirInterface. Results show that no-resource reservation policies increase the utilization of resources and data rates at the expense of increased rate variability across all the users. Moreover, all the policies proposed in this paper outperform state-of-the-art approaches by at least 2×, bringing the waste of resources down to 15%.

Software-Defined Radio Access Networks (SD-RANs), introduced in 5G, represent a paradigm shift in the process of cellular network resource allocation. The decoupling of the control from the data plane, and associating the former with a controller away from Base Stations (BSs), has enabled an increased flexibility in allocating network resources which would lead to performance improvements. However, so far, it is not yet clear to what extent this amelioration ranges in terms of the maximum throughput that can be achieved. Therefore, in this paper, we consider analytically the problem of maximizing the overall network throughput in an SD-RAN environment, by deriving the policy which accomplishes that along with the total throughput, of interest to cellular operators. We assess the performance with real user traces. Results show that the introduction of SD-RAN improves performance by at least 20%.

Software-Defined Radio Access Networks (SD-RANs) foster the concepts of programmability and flexibility, which are vital for next generation cellular networks. However, SD-RANs render network management and orchestration very challenging. Indeed, related works indicate that when thousands of connected devices are spread across the underlying network, SD-RAN approaches with a single controller become deficient and exhibit undesired behavior. Despite this, state-of-the-art research papers lack concrete solutions and evaluations with respect to throughput predictability, where the latter is jeopardized by irregularities in the SD-RAN control plane, specifically in realistic testbeds. In order to overcome the aforementioned issues, in this work, we presentDelphi: a novel platform that provides both analytical and experimental methods to achieve our goal, which is computing the maximum achievable throughput in SD-RAN environments. Analyzing the results provided byDelphi, we can capture the impact of the SD-RAN control plane on throughput. Moreover, we can design important guidelines as to which policy to choose given objectives such as throughput maximization or robustness. Providing a platform for SD-RAN evaluations based on open-source components,Delphienables new avenues for research in the mobile network community. Focusing on FlexRAN SD-RAN controller for our initial results, overall, our findings show that when the number of Base Stations (BSs) and User Equipment (UEs) in the network increases beyond 5000, due to non-timely received control packets for the maximum Channel Quality Indicator (maxCQI) policy the overall throughput decreases by more than 20%.

Next generation radio access networks (RANs) en-vision softwarization and programmability as the main tools to provide the quality of service (QoS) requirements of emerging applications. Consequently, software-defined radio access networks (SD-RANs) have gained increased traction as a technology to foster network management and alleviate orchestration. While there exist SD-RAN architecture concepts both with single and multiple SD-RAN controllers, currently developed prototypes only include a single controller. Such a design may be sufficient for a low number of managed devices, for instance below 50. When the number of devices increases beyond 300, the controller performance deteriorates. A distributed control plane provides a solution, but renders the management in the control plane complex and incurs additional overhead, for instance control handover. In this way, both single controller and distributed control plane approaches may have a negative impact on a user’s QoS. Yet, proper evaluations are missing and therefore the performance remains unclear. In order to investigate the effect of SD-RAN control plane on the user performance, in this work, we provide an extensive evaluation based on a 5G simulator, compliant with 3GPP standardization, as well as measurements with open-source SD-RAN controllers. Based on our simulator, we are able to demystify the user QoS depending on the control plane design choices. Our results demonstrate that having a distributed control plane with control handovers improves the user performance by at least 20% in terms of throughput, 5x regarding the packet loss ratio and 140% in terms of delay compared to a single controller approach. This confirms that the benefits of multiple controllers surpass the overhead caused by more complicated management.

Programmability and softwarization advocate the emerging era of open-source platforms, which embraced by both industry and academia is foreseen as a vital pillar in the construction of next generation mobile networks. Such a valuable open-source project is OpenAirInterface (OAI), which provides a standard compliant mobile network infrastructure, merely based on general purpose hardware computers. While OAI is nowadays widely used by industry and research institutes in proof-of-concept or commercial wireless testbeds, an analysis of the complex functions within the platform is yet to be performed in a large scale. We believe that further research is required to demystify the capabilities of existing tools and present guidelines that alleviate the enhancement and development of additional features. In this context, in this work we shed light on one of the crucial components of any mobile system, namely resource scheduling, while providing an analysis of the available code and instructions to ease the development of new scheduling algorithms based on OAI. Moreover, we demonstrate a performance evaluation of up to 10 UEs for existing and newly implemented scheduling algorithms. Results show, that the development of additional algorithms in OAI is achievable and the experimental behavior follows the theory. Our implementation and observations can serve as a basis for research in the field, and foster the elaboration of theoretical concepts and emerging 5G solutions in practical testbeds.

5G radio access network (RAN) slicing envisions a solution to flexibly deploy heterogeneous services as slices sharing the same infrastructure. However, this level of flexibility renders slice isolation challenging, mainly due to the stochastic nature of wireless resources. In the state-of-the-art, RAN slicing algorithm’s efficiency with respect to slice isolation is related to the ability of meeting individual slice requirements. However, mostly an aggregated slice performance guarantee is considered instead of per user guarantees. Hence, state-of-the-art approaches might not always provide the satisfaction of all users within a slice. Indeed, our results demonstrate that if user requirements within a slice are not included in the RAN slicing algorithm, the per user quality-of-service (QoS) may not be fulfilled. In this paper, we investigate the definition of slice isolation as the ability to satisfy individual users’ throughput within slices, in a frequency selective, multi-cell wireless scenario with focus on maximizing slices’ throughput. Our problem is tackled with a Lyapunov optimization approach, which proves to always achieve slice isolation. Our results show that our solution does not only achieve 100% user QoS guarantees compared to 50% achieved in the state-of-the-art, but also doubles the throughput with increasing number of BSs.

Network edge environments like in-flight or in-train communications utilize satellite-terrestrial integrated networks. These networks however suffer from limited backhaul and cache resources, leading to sustainability issues due to increasing traffic demands. The problem becomes more challenging for 5G ecosystems, where applications have distinct requirements, rendering the management and orchestration of conventional satellite-terrestrial networks harder. Therefore, software-defined networking and edge network slicing are envisioned to enhance resource management and increase flexibility of resource allocation. However, the complexity of management and orchestration increases in cases where service providers, allocated to a slice, do not share information about their users with the infrastructure providers, due to privacy or other concerns. To incorporate the aspect of slice collaboration, we define network slices with respect to their willingness of sharing user traffic statistics with the infrastructure provider. Taking in-flight entertainment and connectivity services (IFECS) as an interesting 5G use-case, we introduce a system model mimicking the practical deployment of slicing for aircrafts using satellites. We propose a mixed integer non linear program that aims at maximizing the number of slices served. Utilizing our model we evaluate the deployment cost of slices with respect to cache and backhaul resources. Our results show that uncooperative slices have a lower selection probability. Nonetheless, we demonstrate that if the slice cost is paid by slice owners, uncooperative slices increase their chances of being served by 33%. Overall, cooperative slicing can revolutionize the IFECS system as it accommodates 200% more slices compared to uncooperative slicing.

Network programmability also sneaked into the mobile world leading to the emergence of Software-Defined Radio Access Network (SD-RAN) architectures. Interestingly, while only a small number of prototype architectures exist for SD-RAN, their performance evaluations are unfortunately also limited. Recent evaluations are carried out for small network dimensions of up to 50 devices, while emerging 5G/6G networks envision numbers of devices beyond 5000. Although 5G/6G applications are more stringent with respect to latency guarantees, performance evaluations of such low scale remain questionable. To fill this void, this paper presentsMARC: a novel benchmarking tool for SD-RAN architectures and their controllers. We useMARCto measure, analyze and identify performance implications for two state-of-the-art open source SD-RAN solutions:FlexRANand5G-EmPOWER. We perceive results for monitoring application scenarios considering fully centralized control. For this setting, our findings show that the proposed architectures with a single SD-RAN controller are not scalable and can even lead to unpredictable network operations. Using our tool and based on our insights, we provide and implement design guidelines for the internal working behavior of the existing controllers.

In the context of the 5G ecosystem, the integration between the terrestrial and satellite networks is envisioned as a potential approach to further enhance the network capabilities. In light of this integration, the satellite community is revisiting its role in the next generation 5G networks. Emerging technologies such as Software-Defined Networking (SDN) which rely on programmable and reconfigurable concepts, are foreseen to play a major role in this regard. Therefore, an interesting research topic is the introduction of management architecture solutions for future satellite networks driven by means of SDN. This anticipates the separation of the data layer from the control layer of the traditional satellite networks, where the control logic is placed on programmable SDN controllers within traditional satellite devices. While a centralized control layer promises delay reductions, it introduces additional overheads due to reconfiguration and migration costs. In this paper, we propose a method to quantify the overhead imposed on the network by the aforementioned parameters while investigating the use-case scenario of an SDN-enabled satellite space segment. We make use of an optimal controller placement and satellite-to-controller assignment which minimizes the average flow setup time with respect to varying traffic demands. Furthermore, we provide insights on the network performance with respect to the migration and reconfiguration cost for our proposed SDN-enabled architecture. Finally, we compare our proposed space segment SDN-enabled architecture with alternative solutions in the state-of-the-art given the aforementioned performance metrics.

Network slicing is envisioned as a tool for 5G networks to provide network flexibility and isolation among different logical networks. While network slicing is well investigated in the fixed-network side, in the Radio Access Network (RAN) there remain challenging problems, which originate mainly from the stochastic nature of the wireless channels and complex resource coupling between slices. In this work, we investigate a network slicing problem for the downlink RAN of a cellular network. Our target is the reduction of resource usage while guaranteeing slice isolation and simultaneously accounting for each slice's average rate and delay requirements. We tackle the problem with a Lyapunov optimization approach, leading to a simple resource assignment procedure that we can prove to achieve isolation while satisfying all slice guarantees. The proposed procedure leads to a functional split, where resources are scheduled within each slice by a slice manager, while a Software-Defined RAN (SD-RAN) controller dynamically re-assigns resources to each slice. We verify our approach through extensive simulations and provide insight on how to fine-tune available system parameters.

Software-Defined Networking (SDN) has been identified as a key enabler for 5G networks to enhance the network capabilities by introducing flexibility and programmability. While SDN has been widely exploited in the core network side, it still remains an open research question in the Radio Access Network (RAN). Initial works highlight the benefits of SDN in RAN and investigate the idea of separating the control plane from the data plane of the Base Stations (BS) by means of SDN. The pioneer Software-Defined RAN (SD-RAN) controllers are available, nonetheless there exist no tools which can shed light on their performance and help to understand their limitations. We introduce SDRBench, a novel SD-RAN controller benchmark tool to fill this void. In this work, we evaluate FlexRAN, which is the first open source SD-RAN platform. In our tool, a Python-based instance of a FlexRAN agent is created and it communicates messages with the controller according to the FlexRAN protocol. The benchmark is used to uncover the limits of the SD-RAN controller.

Software Defined Networking (SDN) has been identified as a potential approach to achieve a more flexible control and management of the traditional satellite systems and enhance the opportunities for future services including the possibility of a hybrid satellite/terrestrial network. Given the renewed interest towards Low-Earth-Orbit (LEO) constellations, an interesting research topic is the design of a suitable network management model taking into account user specific metrics. In this paper, we address this issue while investigating the use-case scenario of an SDN-enabled satellite space segment. A Dynamic Controller Placement Problem (DCPP) is considered for a LEO constellation where the traffic demands change dynamically based on users' geographical position and time zone. To this end, we develop a mathematical model and formulate it as an Integer Linear Programming (ILP) guaranteeing an optimal controller placement and satellite-to-controller assignment minimizing the average flow setup time with respect to the traffic dynamics. We show results for the DCPP regarding the average flow setup time. Furthermore, a comparison with respect to the static approach is investigated and the proposed SDN-enabled LEO constellation architecture is compared with alternative architectures proposed in the state of the art.