An Influence Maximization-Based Hybrid Advertising Dissemination for Internet of Vehicles

Junfang Zheng;Junling Shi;Qiang He;Enchao Zhang;Ammar Hawbani;Liang Zhao
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Abstract

As a key service of the Internet of Vehicles (IoV), vehicle advertising can capture the interest of potential customers and generate revenue for nearby merchants. However, due to the dynamics of vehicles, IoV suffers from unstable communication links between vehicles, which reduces the delivery ratio of vehicle advertising. To address this challenge and progress beyond the state-of-the-art work, this letter adopts Digital Twin (DT) to construct a social relationship model of vehicles and proposes a seed determination scheme for advertising dissemination. On this basis, a Deep Q-network (DQN)-based vehicle advertising dissemination scheme is proposed to determine the updating frequency of the seeds and further improve dissemination efficiency.
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基于影响力最大化的车联网混合广告传播方法
作为车联网(IoV)的一项重要服务,车载广告可以吸引潜在客户的兴趣,并为附近的商家创造收入。然而,由于车辆的动态性,车联网受到车辆间通信链路不稳定的影响,从而降低了车载广告的投放率。为了应对这一挑战并超越最先进的研究成果,本文采用数字孪生(DT)构建了车辆的社会关系模型,并提出了广告传播的种子确定方案。在此基础上,提出了基于深度 Q 网络(DQN)的车辆广告传播方案,以确定种子的更新频率,进一步提高传播效率。
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Table of Contents IEEE Networking Letters Author Guidelines IEEE COMMUNICATIONS SOCIETY IEEE Communications Society Optimal Classifier for an ML-Assisted Resource Allocation in Wireless Communications
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