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  • Open Access

    ARTICLE

    Correlation Composition Awareness Model with Pair Collaborative Localization for IoT Authentication and Localization

    Kranthi Alluri, S. Gopikrishnan*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 943-961, 2024, DOI:10.32604/cmc.2024.048621

    Abstract Secure authentication and accurate localization among Internet of Things (IoT) sensors are pivotal for the functionality and integrity of IoT networks. IoT authentication and localization are intricate and symbiotic, impacting both the security and operational functionality of IoT systems. Hence, accurate localization and lightweight authentication on resource-constrained IoT devices pose several challenges. To overcome these challenges, recent approaches have used encryption techniques with well-known key infrastructures. However, these methods are inefficient due to the increasing number of data breaches in their localization approaches. This proposed research efficiently integrates authentication and localization processes in such a way that they complement each… More >

  • Open Access

    ARTICLE

    Mobile Crowdsourcing Task Allocation Based on Dynamic Self-Attention GANs

    Kai Wei1, Song Yu2, Qingxian Pan1,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 607-622, 2024, DOI:10.32604/cmc.2024.048240

    Abstract Crowdsourcing technology is widely recognized for its effectiveness in task scheduling and resource allocation. While traditional methods for task allocation can help reduce costs and improve efficiency, they may encounter challenges when dealing with abnormal data flow nodes, leading to decreased allocation accuracy and efficiency. To address these issues, this study proposes a novel two-part invalid detection task allocation framework. In the first step, an anomaly detection model is developed using a dynamic self-attentive GAN to identify anomalous data. Compared to the baseline method, the model achieves an approximately 4% increase in the F1 value on the public dataset. In… More >

  • Open Access

    REVIEW

    Review of Collocation Methods and Applications in Solving Science and Engineering Problems

    Weiwu Jiang1, Xiaowei Gao1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 41-76, 2024, DOI:10.32604/cmes.2024.048313

    Abstract The collocation method is a widely used numerical method for science and engineering problems governed by partial differential equations. This paper provides a comprehensive review of collocation methods and their applications, focused on elasticity, heat conduction, electromagnetic field analysis, and fluid dynamics. The merits of the collocation method can be attributed to the need for element mesh, simple implementation, high computational efficiency, and ease in handling irregular domain problems since the collocation method is a type of node-based numerical method. Beginning with the fundamental principles of the collocation method, the discretization process in the continuous domain is elucidated, and how… More >

  • Open Access

    ARTICLE

    Computing Resource Allocation for Blockchain-Based Mobile Edge Computing

    Wanbo Zhang1, Yuqi Fan1, Jun Zhang1, Xu Ding2,*, Jung Yoon Kim3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 863-885, 2024, DOI:10.32604/cmes.2024.047295

    Abstract Users and edge servers are not fully mutually trusted in mobile edge computing (MEC), and hence blockchain can be introduced to provide trustable MEC. In blockchain-based MEC, each edge server functions as a node in both MEC and blockchain, processing users’ tasks and then uploading the task related information to the blockchain. That is, each edge server runs both users’ offloaded tasks and blockchain tasks simultaneously. Note that there is a trade-off between the resource allocation for MEC and blockchain tasks. Therefore, the allocation of the resources of edge servers to the blockchain and the MEC is crucial for the… More >

  • Open Access

    ARTICLE

    A Hybrid and Lightweight Device-to-Server Authentication Technique for the Internet of Things

    Shaha Al-Otaibi1, Rahim Khan2,*, Hashim Ali2, Aftab Ahmed Khan2, Amir Saeed3, Jehad Ali4,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3805-3823, 2024, DOI:10.32604/cmc.2024.049017

    Abstract The Internet of Things (IoT) is a smart networking infrastructure of physical devices, i.e., things, that are embedded with sensors, actuators, software, and other technologies, to connect and share data with the respective server module. Although IoTs are cornerstones in different application domains, the device’s authenticity, i.e., of server(s) and ordinary devices, is the most crucial issue and must be resolved on a priority basis. Therefore, various field-proven methodologies were presented to streamline the verification process of the communicating devices; however, location-aware authentication has not been reported as per our knowledge, which is a crucial metric, especially in scenarios where… More >

  • Open Access

    ARTICLE

    A Deep Reinforcement Learning-Based Technique for Optimal Power Allocation in Multiple Access Communications

    Sepehr Soltani1, Ehsan Ghafourian2, Reza Salehi3, Diego Martín3,*, Milad Vahidi4

    Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 93-108, 2024, DOI:10.32604/iasc.2024.042693

    Abstract For many years, researchers have explored power allocation (PA) algorithms driven by models in wireless networks where multiple-user communications with interference are present. Nowadays, data-driven machine learning methods have become quite popular in analyzing wireless communication systems, which among them deep reinforcement learning (DRL) has a significant role in solving optimization issues under certain constraints. To this purpose, in this paper, we investigate the PA problem in a -user multiple access channels (MAC), where transmitters (e.g., mobile users) aim to send an independent message to a common receiver (e.g., base station) through wireless channels. To this end, we first train… More >

  • Open Access

    ARTICLE

    Micro-Locational Fine Dust Prediction Utilizing Machine Learning and Deep Learning Models

    Seoyun Kim1,#, Hyerim Yu2,#, Jeewoo Yoon1,3, Eunil Park1,2,*

    Computer Systems Science and Engineering, Vol.48, No.2, pp. 413-429, 2024, DOI:10.32604/csse.2023.041575

    Abstract Given the increasing number of countries reporting degraded air quality, effective air quality monitoring has become a critical issue in today’s world. However, the current air quality observatory systems are often prohibitively expensive, resulting in a lack of observatories in many regions within a country. Consequently, a significant problem arises where not every region receives the same level of air quality information. This disparity occurs because some locations have to rely on information from observatories located far away from their regions, even if they may be the closest available options. To address this challenge, a novel approach that leverages machine… More >

  • Open Access

    ARTICLE

    Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

    Thanh-Lam Nguyen1, Hao Kao1, Thanh-Tuan Nguyen2, Mong-Fong Horng1,*, Chin-Shiuh Shieh1,*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2181-2205, 2024, DOI:10.32604/cmc.2024.047387

    Abstract Since its inception, the Internet has been rapidly evolving. With the advancement of science and technology and the explosive growth of the population, the demand for the Internet has been on the rise. Many applications in education, healthcare, entertainment, science, and more are being increasingly deployed based on the internet. Concurrently, malicious threats on the internet are on the rise as well. Distributed Denial of Service (DDoS) attacks are among the most common and dangerous threats on the internet today. The scale and complexity of DDoS attacks are constantly growing. Intrusion Detection Systems (IDS) have been deployed and have demonstrated… More >

  • Open Access

    ARTICLE

    The Effects of Thickness and Location of PCM on the Building’s Passive Temperature-Control–A Numerical Study

    Zhengrong Shi1,3, Jie Ren1, Tao Zhang1,3,*, Yanming Shen2,*

    Energy Engineering, Vol.121, No.3, pp. 681-702, 2024, DOI:10.32604/ee.2023.045238

    Abstract Building energy consumption and building carbon emissions both account for more than 20% of their total national values in China. Building employing phase change material (PCM) for passive temperature control shows a promising prospect in meeting the comfort demand and reducing energy consumption simultaneously. However, there is a lack of more detailed research on the interaction between the location and thickness of PCM and indoor natural convection, as well as indoor temperature distribution. In this study, the numerical model of a passive temperature-controlled building integrating the developed PCM module is established with the help of ANSYS. In which, the actual… More > Graphic Abstract

    The Effects of Thickness and Location of PCM on the Building’s Passive Temperature-Control–A Numerical Study

  • Open Access

    ARTICLE

    Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

    Li Zheng, Gang Xu*, Wenbin Chen

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 935-957, 2024, DOI:10.32604/cmc.2023.046006

    Abstract Drone logistics is a novel method of distribution that will become prevalent. The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption, resulting in cost savings for the company’s transportation operations. Logistics firms must discern the ideal location for establishing a logistics hub, which is challenging due to the simplicity of existing models and the intricate delivery factors. To simulate the drone logistics environment, this study presents a new mathematical model. The model not only retains the aspects of the current models, but also considers the degree of transportation difficulty from the logistics hub to… More >

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