Ho Hai Quan^1,2, Le Huu Binh^1,*, Nguyen Dinh Hoa Cuong³, Le Duc Huy⁴

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075549 - 12 March 2026

Abstract Wireless Sensor Networks (WSNs) play a crucial role in numerous Internet of Things (IoT) applications and next-generation communication systems, yet they continue to face challenges in balancing energy efficiency and reliable connectivity. This study proposes SAC-HTC (Soft Actor-Critic-based High-performance Topology Control), a deep reinforcement learning (DRL) method based on the Actor-Critic framework, implemented within a Software Defined Wireless Sensor Network (SDWSN) architecture. In this approach, sensor nodes periodically transmit state information, including coordinates, node degree, transmission power, and neighbor lists, to a centralized controller. The controller acts as the reinforcement learning (RL) agent, with the… More >

Omar Almomani^1,*, Mahran Al-Zyoud¹, Ahmad Adel Abu-Shareha², Ammar Almomani^3,4,*, Said A. Salloum⁵, Khaled Mohammad Alomari⁶

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2025.075465 - 12 March 2026

Abstract In Wireless Sensor Networks (WSNs), survivability is a crucial issue that is greatly impacted by energy efficiency. Solutions that satisfy application objectives while extending network life are needed to address severe energy constraints in WSNs. This paper presents an Adaptive Enhanced Grey Wolf Optimizer (AEGWO) for energy-efficient cluster head (CH) selection that mitigates the exploration–exploitation imbalance, preserves population diversity, and avoids premature convergence inherent in baseline GWO. The AEGWO combines adaptive control of the parameter of the search pressure to accelerate convergence without stagnation, a hybrid velocity-momentum update based on the dynamics of PSO, and… More >

Mohammad Shokouhifar^1,*, Fakhrosadat Fanian², Mehdi Hosseinzadeh^3,4,*, Aseel Smerat^5,6, Kamal M. Othman⁷, Abdulfattah Noorwali⁷, Esam Y. O. Zafar⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.073789 - 29 January 2026

Abstract Wireless Sensor Networks (WSNs) have become foundational in numerous real-world applications, ranging from environmental monitoring and industrial automation to healthcare systems and smart city development. As these networks continue to grow in scale and complexity, the need for energy-efficient, scalable, and robust communication protocols becomes more critical than ever. Metaheuristic algorithms have shown significant promise in addressing these challenges, offering flexible and effective solutions for optimizing WSN performance. Among them, the Grey Wolf Optimizer (GWO) algorithm has attracted growing attention due to its simplicity, fast convergence, and strong global search capabilities. Accordingly, this survey provides… More >

Ramadan Abdul-Rashid¹, Mohd Amiruddin Abd Rahman^1,*, Abdulaziz Yagoub Barnawi²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3213-3250, 2025, DOI:10.32604/cmes.2025.066589 - 30 September 2025

Abstract Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks (WSNs), especially in security-critical, time-sensitive applications. However, most existing protocols degrade substantially under malicious interference. We introduce iSTSP, an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust, precise synchronization even in hostile environments: (1) trust preprocessing that filters node participation using behavioral trust scoring; (2) anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time; (3) reliability-weighted consensus that prioritizes high-trust nodes during time aggregation; and (4) convergence-optimized synchronization… More >

Valentin Stangaciu^*, Mihai-Vladimir Ghimpau, Adrian-Gabriel Sztanarec

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3213-3229, 2025, DOI:10.32604/cmc.2025.068844 - 23 September 2025

Abstract Along with process control, perception represents the main function performed by the Edge Layer of an Internet of Things (IoT) network. Many of these networks implement various applications where the response time does not represent an important parameter. However, in critical applications, this parameter represents a crucial aspect. One important sensing device used in IoT designs is the accelerometer. In most applications, the response time of the embedded driver software handling this device is generally not analysed and not taken into account. In this paper, we present the design and implementation of a predictable real-time More >

David S. Bhatti^1,*, Annas W. Malik², Haeung Choi¹, Ki-Il Kim^3,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 2157-2177, 2025, DOI:10.32604/cmc.2025.068360 - 29 August 2025

Abstract Traditional chaotic maps struggle with narrow chaotic ranges and inefficiencies, limiting their use for lightweight, secure image encryption in resource-constrained Wireless Sensor Networks (WSNs). We propose the SPCM, a novel one-dimensional discontinuous chaotic system integrating polynomial and sine functions, leveraging a piecewise function to achieve a broad chaotic range () and a high Lyapunov exponent (5.04). Validated through nine benchmarks, including standard randomness tests, Diehard tests, and Shannon entropy (3.883), SPCM demonstrates superior randomness and high sensitivity to initial conditions. Applied to image encryption, SPCM achieves 0.152582 s (39% faster than some techniques) and 433.42 More >

Peng Zhou^1,2, Wei Chen¹, Bingyu Cao^1,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5337-5360, 2025, DOI:10.32604/cmc.2025.065561 - 30 July 2025

Abstract Wireless Sensor Networks (WSNs), as a crucial component of the Internet of Things (IoT), are widely used in environmental monitoring, industrial control, and security surveillance. However, WSNs still face challenges such as inaccurate node clustering, low energy efficiency, and shortened network lifespan in practical deployments, which significantly limit their large-scale application. To address these issues, this paper proposes an Adaptive Chaotic Ant Colony Optimization algorithm (AC-ACO), aiming to optimize the energy utilization and system lifespan of WSNs. AC-ACO combines the path-planning capability of Ant Colony Optimization (ACO) with the dynamic characteristics of chaotic mapping and… More >

Muhammad Salman Qamar^1,*, Muhammad Fahad Munir²

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5463-5485, 2025, DOI:10.32604/cmc.2025.064442 - 30 July 2025

Abstract Wireless Sensor Networks (WSNs) have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes (SNs). However, the operational lifespan of WSNs is significantly constrained by the limited energy resources of SNs. Current energy efficiency strategies, such as clustering, multi-hop routing, and data aggregation, face challenges, including uneven energy depletion, high computational demands, and suboptimal cluster head (CH) selection. To address these limitations, this paper proposes a hybrid methodology that optimizes energy consumption (EC) while maintaining network performance. The proposed approach integrates the Low Energy Adaptive Clustering Hierarchy with Deterministic (LEACH-D) protocol using More >

Xiaogang Yuan^*, Huan Pei, Yanlin Wu

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5555-5575, 2025, DOI:10.32604/cmc.2025.063537 - 30 July 2025

Abstract In the complex environment of Wireless Sensor Networks (WSNs), various malicious attacks have emerged, among which internal attacks pose particularly severe security risks. These attacks seriously threaten network stability, data transmission reliability, and overall performance. To effectively address this issue and significantly improve intrusion detection speed, accuracy, and resistance to malicious attacks, this research designs a Three-level Intrusion Detection Model based on Dynamic Trust Evaluation (TIDM-DTE). This study conducts a detailed analysis of how different attack types impact node trust and establishes node models for data trust, communication trust, and energy consumption trust by focusing… More >

Nimisha Rajput^1,#, Amit Kumar¹, Raghavendra Pal^1,#, Nishu Gupta^2,*, Mikko Uitto², Jukka Mäkelä²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3839-3859, 2025, DOI:10.32604/cmes.2025.065903 - 30 June 2025

Abstract Wireless Sensor Networks (WSNs) play a critical role in automated border surveillance systems, where continuous monitoring is essential. However, limited energy resources in sensor nodes lead to frequent network failures and reduced coverage over time. To address this issue, this paper presents an innovative energy-efficient protocol based on deep Q-learning (DQN), specifically developed to prolong the operational lifespan of WSNs used in border surveillance. By harnessing the adaptive power of DQN, the proposed protocol dynamically adjusts node activity and communication patterns. This approach ensures optimal energy usage while maintaining high coverage, connectivity, and data accuracy. More >