Pralay Roy¹, Pabitra Kumar Biswas¹, Chiranjit Sain^2,*, Taha Selim Ustun^3,*

Energy Engineering, Vol.122, No.10, pp. 4035-4060, 2025, DOI:10.32604/ee.2025.068989 - 30 September 2025

Abstract This study presents the use of an innovative population-based algorithm called the Sine Cosine Algorithm and its metaheuristic form, Quasi Oppositional Sine Cosine Algorithm, to automatic generation control of a multiple-source-based interconnected power system that consists of thermal, gas, and hydro power plants. The Proportional-Integral-Derivative controller, which is utilized for automated generation control in an interconnected hybrid power system with a DC link connecting two regions, has been tuned using the proposed optimization technique. An Electric Vehicle is taken into consideration only as an electrical load. The Quasi Oppositional Sine Cosine method’s performance and efficacy… More >

Surender Singh^1,2,*, Naveen Bilandi^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 489-509, 2025, DOI:10.32604/cmes.2025.065101 - 31 July 2025

Abstract Wireless Body Area Network (WBAN) is essential for continuous health monitoring. However, they face energy efficiency challenges due to the low power consumption of sensor nodes. Current WBAN routing protocols face limitations in strategically minimizing energy consumption during the retrieval of vital health parameters. Efficient network traffic management remains a challenge, with existing approaches often resulting in increased delay and reduced throughput. Additionally, insufficient attention has been paid to enhancing channel capacity to maintain signal strength and mitigate fading effects under dynamic and robust operating scenarios. Several routing strategies and procedures have been developed to… More >

Sarmad K. Ibrahim^1,*, Saif A. Abdulhussien², Hazim M. ALkargole¹, Hassan H. Qasim¹

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5223-5238, 2025, DOI:10.32604/cmc.2025.066548 - 30 July 2025

Abstract The explosive growth of data traffic and heterogeneous service requirements of 5G networks—covering Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communication (URLLC), and Massive Machine Type Communication (mMTC)—present tremendous challenges to conventional methods of bandwidth allocation. A new deep reinforcement learning-based (DRL-based) bandwidth allocation system for real-time, dynamic management of 5G radio access networks is proposed in this paper. Unlike rule-based and static strategies, the proposed system dynamically updates itself according to shifting network conditions such as traffic load and channel conditions to maximize the achievable throughput, fairness, and compliance with QoS requirements. By using… More >

Reem Alkanhel^1,#, Abuzar B. M. Adam^2,#, Samia Allaoua Chelloug¹, Dina S. M. Hassan^1,*, Mohammed Saleh Ali Muthanna³, Ammar Muthanna⁴

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 607-624, 2025, DOI:10.32604/cmc.2025.063206 - 09 June 2025

Abstract The 3GPP standard defines the requirements for next-generation wireless networks, with particular attention to Ultra-Reliable Low-Latency Communications (URLLC), critical for applications such as Unmanned Aerial Vehicles (UAVs). In this context, Non-Orthogonal Multiple Access (NOMA) has emerged as a promising technique to improve spectrum efficiency and user fairness by allowing multiple users to share the same frequency resources. However, optimizing key parameters–such as beamforming, rate allocation, and UAV trajectory–presents significant challenges due to the nonconvex nature of the problem, especially under stringent URLLC constraints. This paper proposes an advanced deep learning-driven approach to address the resulting… More >

Vijaya Krishna Akula^1,*, Tan Kuan Tak², Pravin Ramdas Kshirsagar³, Shrikant Vijayrao Sonekar⁴, Gopichand Ginnela⁵

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2449-2479, 2025, DOI:10.32604/cmc.2025.061486 - 16 April 2025

Abstract The rapid expansion of Internet of Things (IoT) networks has introduced challenges in network management, primarily in maintaining energy efficiency and robust connectivity across an increasing array of devices. This paper introduces the Adaptive Blended Marine Predators Algorithm (AB-MPA), a novel optimization technique designed to enhance Quality of Service (QoS) in IoT systems by dynamically optimizing network configurations for improved energy efficiency and stability. Our results represent significant improvements in network performance metrics such as energy consumption, throughput, and operational stability, indicating that AB-MPA effectively addresses the pressing needs of modern IoT environments. Nodes are More >

Rahma Gantassi, Zaki Masood, Yonghoon Choi^*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 327-343, 2025, DOI:10.32604/cmc.2024.058143 - 03 January 2025

Abstract Wireless sensor network (WSN) technologies have advanced significantly in recent years. Within WSNs, machine learning algorithms are crucial in selecting cluster heads (CHs) based on various quality of service (QoS) metrics. This paper proposes a new clustering routing protocol employing the Traveling Salesman Problem (TSP) to locate the optimal path traversed by the Mobile Data Collector (MDC), in terms of energy and QoS efficiency. To be more specific, to minimize energy consumption in the CH election stage, we have developed the M-T protocol using the K-Means and the grid clustering algorithms. In addition, to improve More >

Adisa Hasković Džubur^*, Samir Čaušević, Belma Memić, Muhamed Begović, Elma Avdagić-Golub, Alem Čolaković

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1059-1084, 2024, DOI:10.32604/cmc.2024.055386 - 15 October 2024

Abstract Wireless sensor networks (WSNs) are characterized by heterogeneous traffic types (audio, video, data) and diverse application traffic requirements. This paper introduces three traffic classes following the defined model of heterogeneous traffic differentiation in WSNs. The requirements for each class regarding sensitivity to QoS (Quality of Service) parameters, such as loss, delay, and jitter, are described. These classes encompass real-time and delay-tolerant traffic. Given that QoS evaluation is a multi-criteria decision-making problem, we employed the AHP (Analytical Hierarchy Process) method for multi-criteria optimization. As a result of this approach, we derived weight values for different traffic… More >

Talal H. Noor^*

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1273-1299, 2024, DOI:10.32604/csse.2024.052510 - 13 September 2024

Abstract In recent years, container-based cloud virtualization solutions have emerged to mitigate the performance gap between non-virtualized and virtualized physical resources. However, there is a noticeable absence of techniques for predicting microservice performance in current research, which impacts cloud service users’ ability to determine when to provision or de-provision microservices. Predicting microservice performance poses challenges due to overheads associated with actions such as variations in processing time caused by resource contention, which potentially leads to user confusion. In this paper, we propose, develop, and validate a probabilistic architecture named Microservice Performance Diagnosis and Prediction (MPDP). MPDP… More >

Darakhshan Syed^*, Ghulam Muhammad, Safdar Rizvi

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 437-476, 2024, DOI:10.32604/iasc.2024.050681 - 11 July 2024

Abstract Cloud Computing has the ability to provide on-demand access to a shared resource pool. It has completely changed the way businesses are managed, implement applications, and provide services. The rise in popularity has led to a significant increase in the user demand for services. However, in cloud environments efficient load balancing is essential to ensure optimal performance and resource utilization. This systematic review targets a detailed description of load balancing techniques including static and dynamic load balancing algorithms. Specifically, metaheuristic-based dynamic load balancing algorithms are identified as the optimal solution in case of increased traffic. More >

Meignanamoorthi Dhandapani^*, V. Vetriselvi, R. Aishwarya

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2449-2486, 2024, DOI:10.32604/cmes.2024.050986 - 08 July 2024

Abstract The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale. Network slicing is crucial in delivering services for different, demanding vertical applications in this context. Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations. However, the existing IP (Internet Protocol) over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators. Conventional inter-domain routing methods, like Border Gateway Protocol (BGP), cannot make routing decisions based on performance,… More >