Seyha Ros^1,#, Seungwoo Kang^1,#, Taikuong Iv¹, Inseok Song¹, Prohim Tam², Seokhoon Kim^1,3,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1649-1665, 2025, DOI:10.32604/cmc.2025.062716 - 16 April 2025

Abstract Recently, Network Functions Virtualization (NFV) has become a critical resource for optimizing capability utilization in the 5G/B5G era. NFV decomposes the network resource paradigm, demonstrating the efficient utilization of Network Functions (NFs) to enable configurable service priorities and resource demands. Telecommunications Service Providers (TSPs) face challenges in network utilization, as the vast amounts of data generated by the Internet of Things (IoT) overwhelm existing infrastructures. IoT applications, which generate massive volumes of diverse data and require real-time communication, contribute to bottlenecks and congestion. In this context, Multi-access Edge Computing (MEC) is employed to support resource… More >

Muhammad Arif^1,*, Muhammad Rashid²

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 13-64, 2025, DOI:10.32604/cmc.2025.062819 - 26 March 2025

Abstract Edge Machine Learning (EdgeML) and Tiny Machine Learning (TinyML) are fast-growing fields that bring machine learning to resource-constrained devices, allowing real-time data processing and decision-making at the network’s edge. However, the complexity of model conversion techniques, diverse inference mechanisms, and varied learning strategies make designing and deploying these models challenging. Additionally, deploying TinyML models on resource-constrained hardware with specific software frameworks has broadened EdgeML’s applications across various sectors. These factors underscore the necessity for a comprehensive literature review, as current reviews do not systematically encompass the most recent findings on these topics. Consequently, it provides… More >

Aiguo Li¹, Yunfei Jia^2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4573-4591, 2025, DOI:10.32604/cmc.2025.059184 - 06 March 2025

Abstract In the context of security systems, adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel. Most studies focus on optimizing base station deployment under the assumption of static obstacles, aiming to maximize the perception coverage of wireless RF (Radio Frequency) signals and reduce positioning blind spots. However, in practical security systems, obstacles are subject to change, necessitating the consideration of base station deployment in dynamic environments. Nevertheless, research in this area still needs to be conducted. This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm (DIE-BDA)… More >

Shumin Li¹, Qifang Luo^1,2,*, Yongquan Zhou^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1955-1994, 2025, DOI:10.32604/cmes.2025.059738 - 27 January 2025

Abstract Wireless sensor network deployment optimization is a classic NP-hard problem and a popular topic in academic research. However, the current research on wireless sensor network deployment problems uses overly simplistic models, and there is a significant gap between the research results and actual wireless sensor networks. Some scholars have now modeled data fusion networks to make them more suitable for practical applications. This paper will explore the deployment problem of a stochastic data fusion wireless sensor network (SDFWSN), a model that reflects the randomness of environmental monitoring and uses data fusion techniques widely used in… More >

Jiaying Shen¹, Donglin Zhu¹, Yujia Liu², Leyi Wang¹, Jialing Hu¹, Zhaolong Ouyang¹, Changjun Zhou¹, Taiyong Li^3,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 345-369, 2025, DOI:10.32604/cmc.2024.060335 - 03 January 2025

Abstract The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life. The development of the Internet of Things (IoT) relies on the support of base stations, which provide a solid foundation for achieving a more intelligent way of living. In a specific area, achieving higher signal coverage with fewer base stations has become an urgent problem. Therefore, this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization (EPSO)… More >

Wanwei Huang^1,*, Qiancheng Zhang¹, Tao Liu², Yaoli Xu¹, Dalei Zhang³

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4875-4893, 2024, DOI:10.32604/cmc.2024.055622 - 12 September 2024

Abstract Aiming at the rapid growth of network services, which leads to the problems of long service request processing time and high deployment cost in the deployment of network function virtualization service function chain (SFC) under 5G networks, this paper proposes a multi-agent deep deterministic policy gradient optimization algorithm for SFC deployment (MADDPG-SD). Initially, an optimization model is devised to enhance the request acceptance rate, minimizing the latency and deploying the cost SFC is constructed for the network resource-constrained case. Subsequently, we model the dynamic problem as a Markov decision process (MDP), facilitating adaptation to the… More >

Wei Zhang¹, Haijun Geng^2,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 427-448, 2024, DOI:10.32604/cmc.2024.051871 - 18 July 2024

Abstract Currently, distributed routing protocols are constrained by offering a single path between any pair of nodes, thereby limiting the potential throughput and overall network performance. This approach not only restricts the flow of data but also makes the network susceptible to failures in case the primary path is disrupted. In contrast, routing protocols that leverage multiple paths within the network offer a more resilient and efficient solution. Multipath routing, as a fundamental concept, surpasses the limitations of traditional shortest path first protocols. It not only redirects traffic to unused resources, effectively mitigating network congestion, but… More >

Umer Nauman¹, Yuhong Zhang², Zhihui Li³, Tong Zhen^1,3,*

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 477-510, 2024, DOI:10.32604/iasc.2024.050726 - 11 July 2024

Abstract Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications. Nevertheless, existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets, such as preservation and server infrastructure, in a limited number of large-scale worldwide data facilities. Optimizing the deployment of virtual machines (VMs) is crucial in this scenario to ensure system dependability, performance, and minimal latency. A significant barrier in the present scenario is the load distribution, particularly when striving for improved energy consumption in a hypothetical grid computing framework. This design… More >

Yuejiao Wang, Zhong Ma^*, Chaojie Yang, Yu Yang, Lu Wei

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 819-836, 2024, DOI:10.32604/cmc.2024.047108 - 25 April 2024

Abstract The quantization algorithm compresses the original network by reducing the numerical bit width of the model, which improves the computation speed. Because different layers have different redundancy and sensitivity to data bit width. Reducing the data bit width will result in a loss of accuracy. Therefore, it is difficult to determine the optimal bit width for different parts of the network with guaranteed accuracy. Mixed precision quantization can effectively reduce the amount of computation while keeping the model accuracy basically unchanged. In this paper, a hardware-aware mixed precision quantization strategy optimal assignment algorithm adapted to… More >

Tarek Sheltami^1,*, Gamil Ahmed¹, Ansar Yasar²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2627-2647, 2024, DOI:10.32604/cmes.2023.044973 - 11 March 2024

Abstract Recently, Internet of Drones (IoD) has garnered significant attention due to its widespread applications. However, deploying IoD for area coverage poses numerous limitations and challenges. These include interference between neighboring drones, the need for directional antennas, and altitude restrictions for drones. These challenges necessitate the development of efficient solutions. This research paper presents a cooperative decision-making approach for an efficient IoD deployment to address these challenges effectively. The primary objective of this study is to achieve an efficient IoD deployment strategy that maximizes the coverage region while minimizing interference between neighboring drones. In deployment problem,… More >