Adeel Iqbal^1,#,*, Muhammad Faisal Siddiqui^2,#,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084851 - 13 August 2026

Abstract Hop-constrained packet routing is a fundamental problem in wireless sensor networks (WSNs), where latency constraints, energy limitations, and practical feasibility requirements greatly restrict routing choices. Traditional methods based on shortest path and greedy routing have low complexity but cannot adapt to dynamic network changes well, while reinforcement learning for routing has the potential to adapt to network variations but has not been well explored in the hard hop-constrained setting. The current study attempts to fill the gap by modeling hop-constrained routing as the decision-making problem in a finite-horizon setting. An integrated simulation environment is proposed… More >

Kiran Saleem¹, Upinder Kaur^2,*, Abdulrahman Mohammed Alamoudi³, Mai Alduailij⁴, Ahmad Subhi Salem Mufleh⁵, Ateeq Ur Rehman^6,*, Salil Bharany⁷

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.083670 - 13 August 2026

Abstract Underwater Wireless Sensor Networks (UWSNs) are exceedingly critical for large-scale underwater applications, such as environmental monitoring, infrastructure inspection, target tracking, and marine surveillance. Nevertheless, network lifetime and communication reliability are severely constrained by harsh underwater acoustic conditions, limited battery power, large propagation delays, node mobility, and uneven energy consumption. In response to these issues, this study proposes a Climate-Aware Hybrid Clustering and Routing (CA-HCR-UWSN) framework to enable sustainable, long-term underwater monitoring. This work proposes a hybrid framework that combines Elephant Herding Optimization (EHO) with the Gravitational Search Algorithm (GSA) to provide an effective solution to… More >

Zhihao Dong^1,2, Huakui Sun^1,2,*, Yueyue Tao², Daosen Zhai²

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.084301 - 23 July 2026

Abstract High-mobility Unmanned Aerial Vehicle (UAV) swarm networks suffer from fast-varying connectivity and interference, and therefore routing decisions must jointly account for link instability and topology changes. By leveraging mobile edge computing (MEC) capabilities, each UAV can perform online routing decisions locally without relying on centralized controllers. This paper develops a Predictive-Q learning framework for dynamic routing under interference and mobility, where the Q-value is trained by a multi-factor reward that explicitly models retransmission costs, predicts link lifetime from relative motion, and anticipates forward connectivity and neighbor redundancy. To further enhance reliability under harsh interference, we More >

Bhanu Talwar^1,*, Puneet Thapar¹, Tahani Alsubait², Mai Alduailij³, Ateeq Ur Rehman^4,*, Salil Bharany⁵

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080977 - 15 June 2026

Abstract Wireless Sensor Networks (WSNs) play a vital role in smart city Internet of Things (IoT) applications, including environmental monitoring, intelligent transportation, and infrastructure management. However, limited battery capacity, uneven energy consumption, and inefficient clustering and routing mechanisms significantly reduce network lifetime, reliability, and scalability, especially in large-scale IoT deployments. Traditional routing protocols often rely on single-objective optimization or static clustering strategies, which fail to maintain long-term energy balance and stable communication performance. To address these challenges, this paper proposes iPAFAR, a Pareto-based multi-objective clustering and routing framework designed for IoT-enabled WSNs. The proposed model formulates… More >

Amjad Rehman¹, Tariq Mahmood^1,2, Faten S. Alamri^3,*, Muhammad I. Khan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.076683 - 27 May 2026

Abstract The rapid deployment of Wireless Sensor Networks (WSNs) faces critical challenges due to sensor nodes’ limited energy and communication capabilities, which restrict network lifetime and data transmission efficiency. Traditional clustering and routing protocols often lead to unbalanced energy consumption and uneven load distribution, whereas intelligent optimization approaches are hindered by high computational costs and slow convergence. This research formulates the clustering and routing problems in WSNs as an optimization challenge under resource and energy constraints, aiming to improve stability, energy efficiency, and throughput. This research proposed three quantum optimization-based solutions to address complex issues. First,… More >

Peiying Zhang^1,2, Yihong Yu^1,2, Jia Luo^3,4,*, Nguyen Gia Ba⁵, Lizhuang Tan^6,7, Lei Shi⁸

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.076690 - 12 March 2026

Abstract Next-Generation Networks (NGNs) demand high resilience, dynamic adaptability, and efficient resource utilization to enable ubiquitous connectivity. In this context, the Space-Air-Ground Integrated Network (SAGIN) architecture is uniquely positioned to meet these requirements. However, conventional NGN routing algorithms often fail to account for SAGIN’s intrinsic characteristics, such as its heterogeneous structure, dynamic topology, and constrained resources, leading to suboptimal performance under disruptions such as node failures or cyberattacks. To meet these demands for SAGIN, this study proposes a resilience-oriented routing optimization framework featuring dynamic weighting and multi-objective evaluation. Methodologically, we define three core routing performance metrics,… More >

Sara Tehsin¹, Inzamam Mashood Nasir^1,*, Wiem Abdelbaki², Fadwa Alrowais³, Khalid A. Alattas⁴, Sultan Almutairi⁵, Radwa Marzouk⁶

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074416 - 10 February 2026

Abstract Objective: Deep learning is employed increasingly in Gastroenterology (GI) endoscopy computer-aided diagnostics for polyp segmentation and multi-class disease detection. In the real world, implementation requires high accuracy, therapeutically relevant explanations, strong calibration, domain generalization, and efficiency. Current Convolutional Neural Network (CNN) and transformer models compromise border precision and global context, generate attention maps that fail to align with expert reasoning, deteriorate during cross-center changes, and exhibit inadequate calibration, hence diminishing clinical trust. Methods: HMA-DER is a hierarchical multi-attention architecture that uses dilation-enhanced residual blocks and an explainability-aware Cognitive Alignment Score (CAS) regularizer to directly align… More >

Mehran Tarif¹, Mohammadhossein Homaei^2,*, Abbas Mirzaei³, Babak Nouri-Moghaddam³

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.071676 - 10 February 2026

Abstract The Routing Protocol for Low-power and Lossy Networks (RPL) is widely used in Internet of Things (IoT) systems, where devices usually have very limited resources. However, RPL still faces several problems, such as high energy usage, unstable links, and inefficient routing decisions, which reduce the overall network performance and lifetime. In this work, we introduce TABURPL, an improved routing method that applies Tabu Search (TS) to optimize the parent selection process. The method uses a combined cost function that considers Residual Energy, Transmission Energy, Distance to the Sink, Hop Count, Expected Transmission Count (ETX), 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 >

Tsu-Yang Wu¹, Chengyuan Yu¹, Yanan Zhao², Saru Kumari³, Chien-Ming Chen^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.069139 - 12 January 2026

Abstract With the increasing complexity of logistics operations, traditional static vehicle routing models are no longer sufficient. In practice, customer demands often arise dynamically, and multi-depot systems are commonly used to improve efficiency. This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand. New customers appear in the delivery process at any time and are periodically optimized according to time slices. Then, we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem. The classical ant colony More >