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FlexVRAN: A Flexible Controller for Virtualized RAN Over Heterogeneous Deployments

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... Moreover, an interesting dynamic end-to-end slicing testbed has been proposed in [15]. In such a testbed, efficient multiservice RAN slice management and orchestration is enabled by automatically adding core networks according to the slice owner's requirements, while a flexible slicing controller for virtualized RAN over heterogeneous deployments has been proposed in [16]. ...
... Moreover, differently from [14], [15], [16], we mainly focus on evaluating the impact of slicing for enabling a more flexible RAN sharing approach from an operator perspective. Our goal is to evaluate if slicing could be employed to add more flexibility in MOCN scenarios, while guaranteeing the same level of isolation provided by MORAN approaches. ...
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In this paper, we present an open source Radio Access Network (RAN) sharing prototype, based on Open Air Interface (OAI) platform, which employs slicing features provided by an open source RAN controller, known as FlexRAN. Accordingly, this paper analyzes the benefits of employing network slicing in the RAN to introduce more flexibility in the configuration of RAN sharing architectures. The contribution of this paper is twofold. Firstly, we propose a flexible RAN sharing architecture where a specific radio slice is allocated to each operator that shares the same RAN, while considering specific Service Level Agreement (SLA) constraints. Secondly, we validate the proposed architecture via a simple radio resource allocation algorithm, which enables dynamic creation and configuration of radio slices, making it possible to transform on-the-fly a “Multi-Operator Core Network” (MOCN) sharing scenario, wherein the spectrum is shared by multiple operators, into a “Multi-Operator RAN” (MORAN) scenario, wherein the spectrum is isolated among the operators that share the same RAN. Emulation results show that the employment of the proposed algorithm enables a more flexible allocation of the radio resources among the sharing operators, providing better performance in terms of end-to-end latency and throughput compared to a static RAN sharing approach.
... Following a similar approach, Papa et al. study the combination of functional split and network slicing in [51]. From a more generic perspective, the authors of [52] propose a framework to handle heterogeneous RAN, functional split selection, and network slicing for multiple services. Finally, the authors of [53] consider split selection together with task offloading, analyzing the interplay of functional split and fog/cloud services. ...
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We study the delay over virtual RAN (vRAN) topologies, entailing base stations that are divided into centralized and distributed units, as well as the packet-switched fronthaul network that connects them. We consider the use of flexible functional split, where the functions that are executed at each of these two entities can be dynamically shifted. We propose a queuing-based model, which is able to precisely mimic the behavior of such nodes, and we validate it by means of extensive simulations. We also exploit Jackson Networks theory to establish the end-to-end delay over the fronthaul network, allowing us to assess the impact of having different networking policies and conditions (for instance, background traffic or heterogeneous technologies). Thanks to the simulator we can also broaden the analysis, by studying the delay variability. In addition, we conduct an in-depth analysis of the performance exhibited by a realistic network setup, whose particular characteristics might hinder the services performance, due to the longer dwell times at each split configuration. The results evince the validity of the proposed model, even under realistic conditions. We show that it might not be enough to guarantee an average stable operation of the centralized/distributed units, but the traffic load should remain below the slowest service rate, to avoid reaching unacceptable delays. An increase of > 100× is observed in the delay, using the realistic network setup, when these conditions do not hold.
... Such approaches have been enabled through the wide application of softwarization for the different network functions, applied even for the Radio Access Network (RAN), and the disaggregation of previous monolithic components (e.g. the cellular core network and the RAN base stations) to separate functions. Efforts like OpenRAN (O-RAN) [1], Software Defined RAN (SD-RAN) [2] and FlexRAN [3] take advantage of such functionalities, and build on them for providing the network operators with advanced functions for the on-the-fly network re-configuration and slicing. In this manner, the network can be dynamically and even autonomously adjusted [4] in an endto-end manner, based on the actual load that it is experiencing, allowing the transition to self-managed and organized 6G networks. ...
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Cloud-native approaches for network functions in the 5G context have been embraced by the community, as they allow flexible management, reconfiguration and monitoring of the network in an end-to-end manner. As network softwarization extends to the RAN, empowered through the cellular stack disaggregation, even base station components can be executed as a cloud-native service. As low latency access is needed in the 5G and beyond networks for serving ultra Reliable Low Latency Communications, Multi-Access Edge Computing (MEC) needs to be integrated in the overall architecture. As the user moves among different RANs, the latency of accessing the service needs to be preserved for providing users with a seamless experience. To accomplish such behavior, migrations of the hosted services are needed, though not fully compatible with the cloud-native approach, and placing them closer to the network access point of the user. In this work, we experiment with a cloud-native end-to-end network, enhanced with Follow-me MEC functionalities. Heterogeneous access is provided at the RAN level, using disag-gregated base stations, and MEC is integrated on the fronthaul of the network, ensuring low-latency access to services. The entire network is instantiated in a cloud-native manner, using a widely adopted container orchestration solution. Our results show that the scheme is able to provide low latency access to the hosted services, while the UE remains agnostic of the entire process and without any drops of the already established connections.
... Resource allocation has recently received significant attention as it is one of the pivot ideas around the slicing concept [36] [37] [38]. Unfortunately, most literature about slicing discusses the resource allocation problem without considering 5G's packet-switched network nature (e.g., segmentation problem where the information is not forwarded unless all the fragments are reassembled), or 5G's RB distribution peculiarities (e.g., RBG). ...
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The 3rd Generation Partnership Project (3GPP) is investing a notable effort to mitigate the endogenous stack and protocol delays (e.g., introducing new numerology, through preemptive scheduling or providing uplink granted free transmission) to attain to the heterogeneous Quality of Service (QoS) latency requirements for which the fifth generation technology standard for broadband cellular networks (5G) is envisioned. However, 3GPP’s goals may become futile if exogenous delays generated by the transport layer (e.g., bufferbloat) and the Radio Link Control (RLC) sublayer segmentation/reassembly procedure are not targeted. On the one hand, the bufferbloat specifically occurs at the Radio Access Network (RAN) since the data path bottleneck is located at the radio link, and contemporary RANs are deployed with large buffers to avoid squandering scarce wireless resources. On the other hand, a Resource Block (RB) scheduling that dismisses 5G’s packet-switched network nature, unnecessarily triggers the segmentation procedure at sender’s RLC sublayer, which adds extra delay as receiver’s RLC sublayer cannot forward the packets to higher sublayers until they are reassembled. Consequently, the exogenously generated queuing delays can surpass 5G’s stack and protocol endogenous delays, neutralizing 3GPP’s attempt to reduce the latency. We address RLC’s related buffer delays and present two solutions: (i) we enhance the 3GPP standard and propose a bufferbloat avoidance algorithm, and (ii) we propose a RB scheduler for circumventing the added sojourn time caused by the packet segmentation/reassembly procedure. Both solutions are implemented and extensively evaluated along with other state-of-the-art proposals in a testbed to verify their suitability and effectiveness under realistic conditions of use (i.e., by considering Modulation and Coding Scheme (MCS) variations, slices, different traffic patterns and off-the-shelf equipment). The results reveal current 3GPP deficits in its QoS model to address the bufferbloat and the contribution of the segmentation/reassembly procedure to the total delay.
... • Prototype: We contribute a prototype SDK implementation, namely ElasticSDK v1.0, which cooperates fully with ElasticSearch (ES) distributed search and analytics engine and Mosaic5G FlexRAN platform [8], [9]. Due to the SDK abstraction, ElasticSDK v1.0 remains applicable to other underlying platforms and can be extended to cover the CN, as well. ...
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Chapter
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