MMIR: a microscopic mechanism for street selection based on intersection records in urban VANET routing

Abstract

In urban vehicular ad hoc networks (VANETs), the intersection-based routing scheme has represented its greater applicability and better efficiency to adapt to high and constrained mobility. How to make an accurate decision for street selection is a challenging issue due to the rapid topology changes in VANETs. In this paper, we propose a microscopic mechanism based on intersection records (MMIR) in which the intersection vehicle nodes maintain and update a records table with every passing vehicle's individual information. By analyzing and processing these entries, we evaluate these vehicles' current positions so as to compute the connectivity probability or estimated delivery delay for all candidate streets to support street selection. In contrast to the statistical and macroscopic information for the common condition, we firstly make use of the individual and microscopic data to enhance the accuracy of estimated results. Furthermore, according to the quantity and the running interval, we classify vehicles into two categories: individual and queue vehicles, in order to effectively decrease the complexity of position estimation. Lastly, since there are no dedicated control packets generated in MMIR, the network overhead is low. The simulation results show that the proposed MMIR outperforms existing approaches of street selection in terms of the accuracy of computed connectivity probability and estimated delay.

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

“…Considering the intersection-based routing mechanism, a microscopic scheme is proposed in [129], where intersecting nodes help maintain and update records by collecting data from passing vehicles. Vehicles' current positions are recorded to compute the connectivity probability and estimate the delivery delay.…”

“…Contributions [37] Uses the probability to estimate the percentage of successful packet delivery to the destination and estimates the current node positions before sending the data [129] Intersecting nodes help maintain and update records by taking data from every passing vehicle, and the delivery delay and vehicles' current positions are recorded to compute the connectivity probability…”