Nada Alasbali^*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4943-4958, 2025, DOI:10.32604/cmc.2025.068330 - 23 October 2025

Abstract Intelligent Traffic Management (ITM) has progressively developed into a critical component of modern transportation networks, significantly enhancing traffic flow and reducing congestion in urban environments. This research proposes an enhanced framework that leverages Deep Q-Learning (DQL), Game Theory (GT), and Stochastic Optimization (SO) to tackle the complex dynamics in transportation networks. The DQL component utilizes the distribution of traffic conditions for epsilon-greedy policy formulation and action and choice reward calculation, ensuring resilient decision-making. GT models the interaction between vehicles and intersections through probabilistic distributions of various features to enhance performance. Results demonstrate that the proposed More >

Zhiyuan Zhang¹, Meng Shuai², Bin Wang¹, Ying He³, Fan Yang¹, Liyan Ren^4,*, Yuyuan Zhang⁴, Ziren Wang⁴

Energy Engineering, Vol.122, No.10, pp. 4169-4194, 2025, DOI:10.32604/ee.2025.066793 - 30 September 2025

Abstract With the rapid development of renewable energy, the Microgrid Coalition (MGC) has become an important approach to improving energy utilization efficiency and economic performance. To address the operational optimization problem in multi-microgrid cooperation, a cooperative game strategy based on the Nash bargaining model is proposed, aiming to enable collaboration among microgrids to maximize overall benefits while considering energy trading and cost optimization. First, each microgrid is regarded as a game participant, and a multi-microgrid cooperative game model based on Nash bargaining theory is constructed, targeting the minimization of total operational cost under constraints such as More >

Mingchen Gao^*

Energy Engineering, Vol.122, No.8, pp. 3243-3263, 2025, DOI:10.32604/ee.2025.065957 - 24 July 2025

Abstract Currently, the international economic situation is becoming increasingly complex, and there is significant downward pressure on the global economy. In recent years, China’s infrastructure sector has experienced rapid growth, with the structure of its power engineering business gradually shifting from traditional infrastructure construction to more diversified areas such as production and operation, as well as emergency repairs. As a result, the transformation of mechanized construction in power transmission and transformation projects has become increasingly urgent. This article proposes a post-evaluation model based on game theory to improve comprehensive weighting and fuzzy grey relational projection sorting,… More > Graphic Abstract

Fatima Asiri¹, Wajdan Al Malwi¹, Fahad Masood², Mohammed S. Alshehri³, Tamara Zhukabayeva⁴, Syed Aziz Shah⁵, Jawad Ahmad^6,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3943-3960, 2025, DOI:10.32604/cmc.2025.066498 - 03 July 2025

Abstract Edge computing (EC) combined with the Internet of Things (IoT) provides a scalable and efficient solution for smart homes. The rapid proliferation of IoT devices poses real-time data processing and security challenges. EC has become a transformative paradigm for addressing these challenges, particularly in intrusion detection and anomaly mitigation. The widespread connectivity of IoT edge networks has exposed them to various security threats, necessitating robust strategies to detect malicious activities. This research presents a privacy-preserving federated anomaly detection framework combined with Bayesian game theory (BGT) and double deep Q-learning (DDQL). The proposed framework integrates BGT… More >

Yiwei Zhang, Xin Cui^*, Qinghui Zhao

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2355-2373, 2025, DOI:10.32604/cmc.2025.065430 - 03 July 2025

Abstract The rapid advance of Connected-Automated Vehicles (CAVs) has led to the emergence of diverse delay-sensitive and energy-constrained vehicular applications. Given the high dynamics of vehicular networks, unmanned aerial vehicles-assisted mobile edge computing (UAV-MEC) has gained attention in providing computing resources to vehicles and optimizing system costs. We model the computing offloading problem as a multi-objective optimization challenge aimed at minimizing both task processing delay and energy consumption. We propose a three-stage hybrid offloading scheme called Dynamic Vehicle Clustering Game-based Multi-objective Whale Optimization Algorithm (DVCG-MWOA) to address this problem. A novel dynamic clustering algorithm is designed… More >

Rongbo Sun, Jinlong Fei^*, Yuefei Zhu, Zhongyu Guo

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3765-3786, 2025, DOI:10.32604/cmc.2025.064849 - 03 July 2025

Abstract Moving Target Defense (MTD) necessitates scientifically effective decision-making methodologies for defensive technology implementation. While most MTD decision studies focus on accurately identifying optimal strategies, the issue of optimal defense timing remains underexplored. Current default approaches—periodic or overly frequent MTD triggers—lead to suboptimal trade-offs among system security, performance, and cost. The timing of MTD strategy activation critically impacts both defensive efficacy and operational overhead, yet existing frameworks inadequately address this temporal dimension. To bridge this gap, this paper proposes a Stackelberg-FlipIt game model that formalizes asymmetric cyber conflicts as alternating control over attack surfaces, thereby capturing More >

Buwei Dang, Huanming Chen^*, Heng Zhang, Jixian Wang, Jian Zhou

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2003-2023, 2025, DOI:10.32604/cmc.2025.062653 - 16 April 2025

Abstract This paper introduces a lane-changing strategy aimed at trajectory planning and tracking control for intelligent vehicles navigating complex driving environments. A fifth-degree polynomial is employed to generate a set of potential lane-changing trajectories in the Frenet coordinate system. These trajectories are evaluated using non-cooperative game theory, considering the interaction between the target vehicle and its surroundings. Models considering safety payoffs, speed payoffs, comfort payoffs, and aggressiveness are formulated to obtain a Nash equilibrium solution. This way, collision avoidance is ensured, and an optimal lane change trajectory is planned. Three game scenarios are discussed, and the More >

Lingqiu Zeng¹, Peibing Sa¹, Qingwen Han², Lei Ye^2,*, Letian Yang¹, Cheng Zhang¹, Jiqiang Cheng²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2059-2086, 2025, DOI:10.32604/cmc.2025.060392 - 16 April 2025

Abstract Congestion control is an inherent challenge of V2X (Vehicle to Everything) technologies. Due to the use of a broadcasting mechanism, channel congestion becomes severe with the increase in vehicle density. The researchers suggested reducing the frequency of packet dissemination to relieve congestion, which caused a rise in road driving risk. Obviously, high-risk vehicles should be able to send messages timely to alarm surrounding vehicles. Therefore, packet dissemination frequency should be set according to the corresponding vehicle’s risk level, which is hard to evaluate. In this paper, a two-stage fuzzy inference model is constructed to evaluate More >

Haiyan Sun^1,*, Chenglong Shao¹, Jianwei Zhang¹, Kun Wang², Wanwei Huang¹

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1451-1470, 2025, DOI:10.32604/cmc.2025.059724 - 26 March 2025

Abstract To address the problem that existing studies lack analysis of the relationship between attack-defense game behaviors and situation evolution from the game perspective after constructing an attack-defense model, this paper proposes a network attack-defense game model (ADGM). Firstly, based on the assumption of incomplete information between the two sides of the game, the ADGM model is established, and methods of payoff quantification, equilibrium solution, and determination of strategy confrontation results are presented. Then, drawing on infectious disease dynamics, the network attack-defense situation is defined based on the density of nodes in various security states, and… More >

Jianhua Liu^*, Jincheng Wei, Rongxin Luo, Guilin Yuan, Jiajia Liu, Xiaoguang Tu

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1337-1361, 2024, DOI:10.32604/cmc.2024.056286 - 15 October 2024

Abstract With the rapid advancement of Internet of Vehicles (IoV) technology, the demands for real-time navigation, advanced driver-assistance systems (ADAS), vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, and multimedia entertainment systems have made in-vehicle applications increasingly computing-intensive and delay-sensitive. These applications require significant computing resources, which can overwhelm the limited computing capabilities of vehicle terminals despite advancements in computing hardware due to the complexity of tasks, energy consumption, and cost constraints. To address this issue in IoV-based edge computing, particularly in scenarios where available computing resources in vehicles are scarce, a multi-master and multi-slave double-layer game model More >