LACCVoV: Linear Adaptive Congestion Control With Optimization of Data Dissemination Model in Vehicle-to-Vehicle Communication

Vehicle-to-vehicle communication assists road-side information exchange granting ease of access and sharing between users. The communication between the vehicles is short-lived due to interference and data congestion in the resource constraint medium. This manuscript introduces a linear adaptive congestion control (LACC) augmenting the benefits of greedy routing and data dissemination model (DDM). LACC focuses on selecting beneficiary vehicle by assessing its end-to-end service capacity and link stability preference. Different from the conventional greedy approach, routing is aided by a linear integer programming module for smart decisions on neighbor selection. The interrupts in data transmission and forwarding due to non-localized vehicles, congested routing paths and paused transmissions are addressed using LACC as a series of linear optimization. This helps to improve the performance of vehicular communication estimated using delay, message delivery, outage, and beacon messages.

Automated summary

The manuscript introduces a linear adaptive congestion control (LACC) method that focuses on selecting beneficiary vehicles by assessing their service capacity and link stability preference. It aids routing decisions using a linear integer programming module for smart neighbor selection, addressing interruptions and congestion issues in vehicular communication. This approach aims to improve communication performance by optimizing delay, message delivery, outage, and beacon messages.