Team ADOPNET Advanced Technologies for Operated Networks

networks as signalling related to mobility management represents a more and more important part of the total tra(cid:30)c. It is also useful for the analysis of the performance of complex link layer protocols in radio networks. our solution dynamically adapts the selected path across time avoiding overexploited e(cid:30)cient links as well as low throughput link usage. This adaptation is performed considering each link state and the amount of channel information available. This improves the throughput and delay with only small marginal overhead cost. Our proposal applies to all wireless multihop networks, with increased bene(cid:28)t for extending cell coverage. We demonstrate through our simulation study that our solution raises the system capacity by more than 50 percents in several scenarii as well as reduces packet delays compared to state-of-the-art protocols such as Ad-hoc On-demand Distance Vector (AODV), Optimized Link State Routing (OLSR) and Link State Opportunistic Routing (LSOR). Abstract: Arti(cid:28)cial Intelligence and Machine learning have been successfully applied to various domains. This success suggests that these techniques could be successfully applied in the context of wireless networks to improve the overall performance and e(cid:30)ciency. AI4Green is built around the need to build compre-hensive, sophisticated and energy-e(cid:30)cient algorithms and solutions at both radio access and core networks, but also on data centres and storage while keeping in mind the emergence of new architectures and the development of smart grids. Abstract: The participants in the "Beyond 5G" program will work together for three years to design technical solutions for the development of sovereign and secure next-generation 5G networks, while developing innovative uses for the industry of the future. The project goes far beyond a simple technical improvement by paving the way for a wide range of industrial uses based on new cognitive, predictive and contextual capabilities in order to provide an unprecedented experience. The project teams will also focus on post-5G developments, which will be driven by the introduction of disruptive technologies with severe constraints in terms of digital security. Abstract: The main objective of SPIDER is to develop an Autonomous cyber defense against Internet threats for 5G private networks. In order to reach this aim, 4 main drivers will be considered: The Abstract: The Maya project deals with the optimisation of meshed wireless networks when there is no infrastructure (natural disaster, desert zone). The approach is to use learning methods when possible. Abstract: The WEC-UP project proposes to build optimized, cooperative and coordinated Networks and Edge Clouds for verticals. The architecture enables the network to evolve into an E2E Cloud Native infrastructure that integrates 5G NR RAN, 5G Core network and EDGE computing. The project The goal is to study propose Abstract: The objective of the thesis is to analyze the performance of unicast and multicast/broadcast modes and to study how to combine them in a really hybrid mode in order to maximize the quality of service while limiting the radio resource that is used. Abstract: Even with dense base station deployments, public transport users often have a low quality for mobile services. Due to the insulation of the vehicle, passengers experience little to no connectivity on their end devices and low data bit rate. The objective of the project is to propose a mobile relay architecture for LTE and to study how it can be adapted and optimized for 5G.