Vehicle interconnection metric and clustering protocol for improved connectivity in vehicular ad hoc networks

Abstract

Communication is the main driving force behind the emerging intelligent transportation systems, which are expected to make traveling safer, more ecological, and faster. The most challenging among all the different communication technologies that will be used are the direct vehicle-to-vehicle communications, because vehicles move with high speeds and in different directions. Apart from that, it is expected that vehicles should be able to organize themselves in an ad hoc network without any assistance from outside entities, such as road side units. To make the ad hoc network less dynamic and communications more reliable, vehicles with similar movement patterns can be grouped together in clusters. Clustering is a well-known method for organizing ad hoc networks and is used in mobile and wireless sensor networks, but with different constraints and goals, so new clustering solutions for vehicular ad hoc networks (VANET) have to be developed. In recent years, this has been a hot topic among researchers and many different clustering algorithms for VANET have been proposed. In this paper, we propose a new clustering metric for VANET, named vehicle interconnection metric, which is based on sending periodic beacons among vehicles and reflects the communication abilities between them. We also propose a new clustering algorithm whose primary goal is increased connectivity and lower number of disconnects. The working principle of this algorithm is also inverted compared to others and uses unneeded cluster head elimination instead of cluster head election. Mathematical analysis of memory usage and communication overhead are provided, predicting low-resource usage. Simulation results, obtained with the ns-3 network simulator and the SUMO vehicle movement simulator, have confirmed the analysis and expected performance in terms of cluster head duration, number of connectivity losses and role switches.

SOFCluster: Safety‐oriented, fuzzy logic‐based clustering scheme for vehicular ad hoc networks

“…Many intelligent clustering schemes for VANETs were elaborated. 12,[24][25][26] Unfortunately, all these works apply passive intervehicle distances as one of main metrics used to select CHs. That is, these distances do not take into consideration the safe intervehicle distances which assist drivers to avoid collisions thus generating clusters' instability and frequent CHs reelections leading to higher overheads.…”

An effective handover management based on SINR and software‐defined network over urban vehicular ad hoc networks

“…The SDN controller sends the precise forwarding rules to the vehicles and RSUs that assist them to allocate the certain resources for different traffic flows related to distinct aspects (safety, efficiency, comfort, etc). Due to the limitation of vehicles mobility and motion range in UVANET, RSU‐based clustering is perceived as a promising solution in reducing the handover failure and ensuring effective communication quality . Initially, the proposed system assumes that the RSU will work as a CH while vehicles that are located in the transmission range of RSU will function as cluster members.…”