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International audience; With the proliferation of use-cases envisioned to be supported by 5G networks, the focus is not only on the performance, but also on the service agility and elasticity. Cloud native principal is a methodology of designing lightweight, isolatedcontext, and deployable at scale applications that natively exploit the features of cloud. However, supporting telco applications (e.g., 4G/5G services) in the cloud brings up many challenges, such as the coexistence of physical and virtual functions, (near) realtime resource provisioning, service continuity, and strict latency and data rates. In this paper, we propose Kube5G, as a realizable agile service platform in support of 4G/5G cloud native applications. Kube5G introduces a novel approach in building and packaging a cloud-native compliant telco network function (NF) in a form of nested well-defined layers. In addition, we present a workflow for continuous integration and development operations in support of multi-version network functions (physical, virtual and cloud functions). We also present a concrete prototype implementation of Kube5G with experimental results indicating its efficiency and highlighting user and network perceived performance.

In this demo, we present 5G network automation in cloud-native environment. Our proposition is to demonstrate the network automation using Kubernets as container orchestration and automating application deployment, while using Openshift Operator as a tool to manage complex services, such as 5G services. For this purpose, we use the containerized OpenAirInterface (OAI) to deploy the network and demonstrate the automatability, such as dynamic switch of RAN between monolithic base station and disaggregated RAN (i.e. Distributed Unit-DU and Centralized Unit-CU), and auto-configuration.

Next generation cellular networks (5G) have to deal with massive deployment of machine-type-communication (MTC) devices, expected to cause congestion and system overload in both the radio access network (RAN) and the core network (CN). Moreover, not only would the network suffer from the system overload, but also the MTC devices would experience high latency to access the channel and high power consumption due to the retransmission attempts. Indeed, power consumption is a critical issue in MTC, as the devices are not plugged into the electrical supply, e.g., in the case of sensor devices. To alleviate system overload (caused by the massive MTC deployment), the 3GPP proposed the group paging (GP) method. However, its performances dramatically decrease when increasing the number of MTC devices being paged. In this paper, we devise a novel method, named further improvement-traffic scattering for group paging (FI-TSFGP), which aims to improve the performance of GP when the number of MTC devices is high. FI-TSFGP scatters the paging operation of the MTC devices over a GP interval instead of letting all of the devices start the channel access procedure at nearly the same time. By doing so, FI-TSFGP achieves high-channel access probability for MTC devices, leading to the reduction of both the channel access latency and power consumption. Compared to GP and two other schemes, simulation results clearly demonstrate the high performance of FI-TSFGP in terms of: success and collision probabilities, average access delay, average number of preamble transmissions, and ultimately energy conservation.

International audience; In this paper, we propose a network planning and provisioning framework that optimizes deployment cost in C-RAN based 5G networks. Our framework is based on a Mixed Integer Quadratically Constrained Programming (MIQCP) model which optimizes " virtualized " 5G service chain deployment cost while performing adequate provisioning to address user demand and performance requirements. We use two realistic scenarios to showcase that our framework can be applied to different types of deployments and discuss the computational cost and scalability of our solution.

International audience; Ultra Dense Networks (UDNs) are a natural deployment evolution for handling the tremendous traffic increase related to the emerging 5G services, especially in urban environments. However, the associated infrastructure cost may become prohibitive. The evolving paradigm of network slicing can tackle such a challenge while optimizing the network resource usage, enabling multi-tenancy and facilitating resource sharing and efficient service-oriented communications. Indeed, network slicing in UDN deployments can offer the desired degree of customization in both vanilla Radio Access Network (RAN) designs, but also in the case of disaggregated multi-service RANs. In this article, we devise a novel multi-service RAN environment, i.e., RAN runtime, capable to support slice orchestration procedures and to enable flexible customization of slices as per tenant needs. Each network slice can exploit a number of services, which can either be dedicated or shared between multiple slices over a common RAN. The novel architecture we present concentrates on the orchestration and management systems. It interacts with the RAN modules, through the RAN runtime, via a number of new interfaces enabling a customized dedicated orchestration logic for each slice. We present results for a disaggregated UDN deployment where the RAN runtime is used to support slice-based multi-service chain creation and chain placement, with an auto-scaling mechanism to increase the performance.

International audience; Machine-Type-Communication (MTC) is a promisingservice of the envisioned 5G mobile networks. However,deploying a massive number of MTC devices in these networksremains a challenge due to the overload that may appear atthe Radio Access Network (RAN), hence degrading the Qualityof Services (QoS) for both MTC and Non-MTC devices. Oneof the methods used to address the congestion’s problem inRAN is Group Paging (GP), wherein a single message is usedto activate a group of devices. Whilst the GP method has severaladvantages, its performance quickly decreases when the numberof MTC devices increases. In this paper, we devise a new method,namely Traffic Scattering For Group Paging (TSFGP) to improvethe performance of the GP method for massive deployment ofMTC devices. Numerical results demonstrate that TSFGP highlyimproves the performance of GP in terms of several performancemetrics, such as success probability, collision probability, andaccess delay.

International audience; In this paper we propose a novel algorithm, namely Multi-Objective Placement (MOP), for the efficient placement of Virtualized Network Function (VNF) chains in future 5G systems. Real datasets are used to evaluate the performance of MOP in terms of acceptance ratio and embedding time when placing the time critical radio access network (RAN) functions as a chain. In addition, we rely on a realistic infrastructure topology to assess the performance of MOP with two main objectives: maximizing the number of base stations that could be embedded in the Cloud and load balancing. The results reveal that the acceptance ratio of embedding RAN functions is only 5% less than the one obtained with the optimal solution for the majority of considered scenarios, with a speedup factor of up to 2000 times.