Le Déploiement Optimal des Stations de Base Routières dans un Réseau Véhiculaire ad-hoc

Abstract

Recently, road safety and vehicle security are enhanced using a networking technology known as Vehicular Ad hoc Network (VANET), aiming at serving digital needs of car drivers and passengers. One of the most important challenges of VANETs is the high dynamic of network topology, often leading to intermittent transmissions. To cope with this issue, stationary nodes called roadside unit (RSU)are conceived as VANET infrastructure-based components to play a crucial role in VANET in order to provide continuous transmission coverage and permanent connectivity. However, deploying RSUs involves additional investment and maintenance costs, which implies leading new research activities to optimally place a limited number of RSUs in a given road traffic area to achieve maximum network performance. Precisely, RSUs placement is described as the process of finding the best combination of RSUs on the adequate intersections in order to improve VANET performance in terms of network connectivity. The works presented in this thesis quantifies the benefits of Roadside Unit deployments and proposes innovative approaches to optimize the placement of RSUs set that is able to maximize network performance with a reduced cost. The first part of the thesis focuses on state of the art: First, the way how the information is collected, stored, and harvested using vehicle-to-infrastructure (V2I) communication is reviewed. The proposed survey distinguished two main categories of VANET RSU deployment;namely static and dynamic deployment based on the mobility of vehicles. Also, a comparison between the existing RSU deployment schemes proposed in the literature based on different networking metrics are presented and discussed. Our comparative study confirms that the performance of the proposed RSU placement systems is compromised by several factors such as roads shape, particularity, road segments like frequently occurring accident areas, wireless access methods, moiibility model, vehicles distribution over time and space. Finally, this survey is concluded by presenting some future research directions in this domain. In addition to what has been presented, we suggest a new genetic intersection-coverage algorithm (GICA) based on the priority concept. GICA considers putting RSUs within the most popular intersection aiming to maximize the connectivity between RSUs and at the same time to minimize the interference rate and RSUs costs. After a set of simulations and comparisons to the conventional greedy approach, the obtained results demonstrated that GICA ensures the largest network connectivity with a minimum number of RSUs placed in the tested area with a reduced overlapping ratio. The last part of the thesis focuses on the RSUs deployment formulation issue as a maximum intersection coverage problem through a graph-based modeling. Moreover, we propose a new bio-inspired RSU placement system called Ant colony optimization system for RSU deployment in VANET (AC-RDV). AC-RDV is based on the idea of placing RSUs within the more popular road intersections, which are close to popular places like touristic and commercial areas. Since RSU deployment problem is considered as NP-Hard, AC-RDV inspires by the foraging behavior of real ant colonies to discover the minimum number of RSU intersections that ensures the maximum network connectivity. After a set of simulations and comparisons to traditional RSU placement strategies, the results obtained showed the effectiveness of the proposed AC-RDV in terms of number of RSUs placed, the average area coverage, the average connectivity and the overlapping ratio.