Ultra Reliable, Low Latency Vehicle-to-Infrastructure Wireless Communications with Edge Computing
Md Mostofa Kamal Tareq, Omid Semiari, Mohsen Amini Salehi, and Walid, Saad

TL;DR
This paper introduces a novel algorithm that optimizes vehicle-to-infrastructure association and bandwidth allocation to enhance reliability and reduce latency in autonomous vehicle communications using edge computing.
Contribution
It presents a distributed association and resource allocation framework leveraging labor market tools, with proven convergence and improved performance over traditional schemes.
Findings
Significant reduction in end-to-end latency.
Enhanced network reliability for autonomous vehicles.
Outperforms conventional association schemes in simulations.
Abstract
Ultra reliable, low latency vehicle-to-infrastructure (V2I) communications is a key requirement for seamless operation of autonomous vehicles (AVs) in future smart cities. To this end, cellular small base stations (SBSs) with edge computing capabilities can reduce the end-to-end (E2E) service delay by processing requested tasks from AVs locally, without forwarding the tasks to a remote cloud server. Nonetheless, due to the limited computational capabilities of the SBSs, coupled with the scarcity of the wireless bandwidth resources, minimizing the E2E latency for AVs and achieving a reliable V2I network is challenging. In this paper, a novel algorithm is proposed to jointly optimize AVs-to-SBSs association and bandwidth allocation to maximize the reliability of the V2I network. By using tools from labor matching markets, the proposed framework can effectively perform distributed…
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Taxonomy
TopicsVehicular Ad Hoc Networks (VANETs) · IoT and Edge/Fog Computing · Wireless Body Area Networks
