Optimizing CP-ABE Decryption in Urban VANETs: A Hybrid Reinforcement Learning and Differential Evolution Approach

IF 6.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Open Journal of the Communications Society Pub Date : 2024-10-11 DOI:10.1109/OJCOMS.2024.3479069
Muhsen Alkhalidy;Mohammad Bany Taha;Rasel Chowdhury;Chamseddine Talhi;Hakima Ould-Slimane;Azzam Mourad
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Abstract

In urban environments, efficiently decrypting CP-ABE in VANETs is a significant challenge due to the dynamic and resource-constrained nature of these networks. VANETs are critical for ITS that improve traffic management, safety, and infotainment through V2V and V2I communication. However, managing computational resources for CP-ABE decryption remains difficult. To address this, we propose a hybrid RL-DE algorithm. The RL agent dynamically adjusts the DE parameters using real-time vehicular data, employing Q-learning and policy gradient methods to learn optimal policies. This integration improves task distribution and decryption efficiency. The DE algorithm, enhanced with RL-adjusted parameters, performs mutation, crossover, and fitness evaluation, ensuring continuous adaptation and optimization. Experiments in a simulated urban VANET environment show that our algorithm significantly reduces decryption time, improves resource utilization, and enhances overall efficiency compared to traditional methods, providing a robust solution for dynamic urban settings.
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优化城市 VANET 中的 CP-ABE 解密:强化学习与差分进化混合方法
在城市环境中,由于 VANET 的动态性和资源有限性,在 VANET 中高效解密 CP-ABE 是一项重大挑战。VANET 对于通过 V2V 和 V2I 通信改善交通管理、安全和信息娱乐的智能交通系统至关重要。然而,管理 CP-ABE 解密的计算资源仍然很困难。为此,我们提出了一种混合 RL-DE 算法。RL 代理利用实时车辆数据动态调整解密参数,并采用 Q-learning 和策略梯度法来学习最优策略。这种整合提高了任务分配和解密效率。利用 RL 调整参数增强的 DE 算法可执行突变、交叉和适应性评估,确保持续适应和优化。在模拟城市 VANET 环境中进行的实验表明,与传统方法相比,我们的算法大大缩短了解密时间,提高了资源利用率和整体效率,为动态城市环境提供了稳健的解决方案。
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来源期刊
CiteScore
13.70
自引率
3.80%
发文量
94
审稿时长
10 weeks
期刊介绍: The IEEE Open Journal of the Communications Society (OJ-COMS) is an open access, all-electronic journal that publishes original high-quality manuscripts on advances in the state of the art of telecommunications systems and networks. The papers in IEEE OJ-COMS are included in Scopus. Submissions reporting new theoretical findings (including novel methods, concepts, and studies) and practical contributions (including experiments and development of prototypes) are welcome. Additionally, survey and tutorial articles are considered. The IEEE OJCOMS received its debut impact factor of 7.9 according to the Journal Citation Reports (JCR) 2023. The IEEE Open Journal of the Communications Society covers science, technology, applications and standards for information organization, collection and transfer using electronic, optical and wireless channels and networks. Some specific areas covered include: Systems and network architecture, control and management Protocols, software, and middleware Quality of service, reliability, and security Modulation, detection, coding, and signaling Switching and routing Mobile and portable communications Terminals and other end-user devices Networks for content distribution and distributed computing Communications-based distributed resources control.
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