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Providing a high level of Quality of Service is essential for future wireless networks. This article presents a new multihop wireless routing protocol that opportunistically takes profit from variations of radio conditions in terms of path loss, shadowing and multipath fading to maximize the system capacity. However, guaranteeing high system capacity should not evade the packet delay minimization objective. Consequently, the best path should not only be considered as the path with best throughput but a combination of a good link throughput and, in addition, low router buffer occupancy load. Taking into account the available router buffer occupancy in its path selection, our proposal uses queuing theory information in order to also provide an efficient load balancing solution that adequately distributes the traffic load in the whole network. Exploiting this information, our solution dynamically adapts the selected path across time avoiding overexploited efficient 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 benefit for extending cell coverage. We demonstrate through our simulation study that our solution raises the system capacity by more than 50% in several scenarii as well as reduces packet delays compared to state-of-the-art protocols such as Ad-hoc On-demand Distance Vector, Optimized Link State Routing and Link State Opportunistic Routing. [ABSTRACT FROM AUTHOR]

The ever increasing amount of connected mobile devices and users in the Internet of vehicles and the fact bicycles, electric scooters and users' smartphones are also connected poses a real challenge in terms of ensuring quality of service. The constantly changing topology due to the high‐mobility of devices and users greatly impacts its stability and the connectivity of devices. Furthermore, to ensure safety of people in the case of autonomous vehicles it is of paramount importance to ensure excellent reliability. This is why we have developed a solution that is based on machine learning to classify devices according to their mobility profile and that uses a scoring system to select the best candidates to act as mobile relays amongst devices with a suitable mobility profile. The scoring system allows to find critical locations in terms of user density. This solution does not require a dedicated infrastructure such as road side units. Simulations results will show the proposed solution increases the packet delivery ratio by up to 6%, reduces the energy consumption by up to 30% and increases the efficiency of bandwidth usage without sacrificing the end delay of users and devices compared with the state‐of‐the‐art. [ABSTRACT FROM AUTHOR]

Since the last few years, the Internet of Vehicles (IoV) has gained more interest from the community because of the rapid development of autonomous vehicles, the growing amount of data generated by vehicles' sensors, and the motivation to use this data for different purposes. Given the very dynamic nature of fast moving vehicles, building a network that guarantees the Quality of Service (QoS) is still a challenge. This is why we have developed an original architecture and a programmable objective function to improve QoS on the ever‐changing networks present in the IoV. Simulation results will show that the proposed solution adapts better to mobility by providing better packet delivery ratio up to five times, achieving three times less packet losses and greatly reducing the energy consumption by a factor 10 compared with state of the art solutions, without compromising delay nor throughput usage. [ABSTRACT FROM AUTHOR]

Enhancing the quality of service is the crucial issue of future wireless networks. In this paper, we propose a new multihop wireless routing protocol inspired by opportunistic resource allocation strategies that take into account the variability of the radio conditions due to path loss, shadowing and multipath fading. Thanks to this knowledge, our proposition dynamically adapts the selected path accross time. The adaptation is function of each link state and the amount of channel information available. This allows to improve system performance in terms of delay and throughput. This solution can be used in all multihop wireless contexts but can have a special interest in wireless coverage zone extension context. Simulation results will show that the proposed routing protocol greatly outperforms the other existing protocols such as ad-hoc on-demand distance vector, optimized link state routing and extremely opportunistic routing protocols reducing mean packet delays by more than 50% in several scenarii. [ABSTRACT FROM AUTHOR]