# A Cooperative Content Dissemination Framework for Fog-Based Internet of Vehicles

## TL;DR

This paper introduces a novel framework for content dissemination in fog-based Internet of Vehicles, modeling resource dynamics over time and proposing algorithms to optimize scheduling and resource management under mobility challenges.

## Contribution

It presents a time-varying resource relationship graph and decomposes the complex optimization into manageable subproblems with tailored algorithms for efficient content dissemination.

## Key findings

- Proposed algorithms outperform existing methods in simulations.
- Effective handling of mobility and resource variability improves QoS.
- Robust resource management accounts for channel uncertainties.

## Abstract

As the fog-based internet of vehicles (IoV) is equipped with rich perception, computing, communication and storage resources, it provides a new solution for the bulk data processing. However, the impact caused by the mobility of vehicles brings a challenge to the content scheduling and resource allocation of content dissemination service. In this paper, we propose a time-varying resource relationship graph to model the intertwined impact of the perception, computation, communication and storage resources across multiple snapshots on the content dissemination process of IoV. Based on this graph model, the content dissemination process is modeled as a mathematical optimization problem, where the quality of service of both delay tolerant and delay sensitive services are considered. Owing to its NP-completeness, the optimization problem is decomposed into a joint link and subchannel scheduling subproblem and as well a joint power and flow control subproblem. Then, a cascaded low complexity scheduling algorithm is proposed for the joint link and subchannel scheduling subproblem. Moreover, a robust resource management algorithm is developed for the power and flow control subproblem, where the channel uncertainties in future snapshots are fully considered in the algorithm. Finally, we conduct simulations to show that the effectiveness of the proposed approaches outperforms other state-of-art approaches.