Abstract:
Uncertain link states and the presence of dynamic vehicular topologies pose significant
challenges in Software-Defined Vehicular Networks (SDVNs) when considering
the reliability of data delivery. Current methods fail to model uncertainty and
estimate link lifetime accurately; therefore, the risk of packet loss is greater. In addition,
they do not compute optimal flow fractions based on sub-flow throughput,
energy consumption, latency, and packet delivery ratio, nor do they consider the
effect of flow interactions. In this study, an original link lifetime estimation model
is proposed along with an optimization-based multipath flow routing framework.
The optimization model is formulated as a nonlinear optimization problem with
the aim of optimizing flow delivery with the objectives of maximizing throughput
and packet delivery ratio while minimizing latency and packet transmission
energy. The proposed framework aims to model the effect of flow interactions
in the optimization model to capture the effects of congestion and interference
among different flows. Through the introduction of constraints for heterogeneous
channel utilization, the proposed framework aims to avoid network congestion,
while Quality of Service (QoS) threshold constraints guarantee a QoS-aware routing
solution, ensuring data integrity and reliability. Prediction of link lifetime
uses probability-based methods incorporating vehicle mobility scenarios, such as
approaching/leaving junctions or other nearby vehicles, with corresponding sensor
data like relative velocity and acceleration. The link lifetime modeling includes
the effects of vehicular density and propagation path loss on link stability and is
derived using the Cost-231 path loss model for line-of-sight and non-line-of-sight
scenarios with urban building obstructions. Our study evaluates the proposed
routing framework against existing approaches in terms of delivery ratio, latency,
energy consumption, and throughput for different speeds and flow sizes. The results
demonstrate the superiority of the proposed framework with a consistent
packet delivery ratio of 98–100% and much lower latency (10–15 ms) compared
to benchmark schemes (e.g., QRSDN at 60% delivery and 80 ms latency), while
maintaining stable throughput.
