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  • Open Access

    ARTICLE

    A Comprehensive Study of Resource Provisioning and Optimization in Edge Computing

    Sreebha Bhaskaran*, Supriya Muthuraman

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5037-5070, 2025, DOI:10.32604/cmc.2025.062657 - 19 May 2025

    Abstract Efficient resource provisioning, allocation, and computation offloading are critical to realizing low-latency, scalable, and energy-efficient applications in cloud, fog, and edge computing. Despite its importance, integrating Software Defined Networks (SDN) for enhancing resource orchestration, task scheduling, and traffic management remains a relatively underexplored area with significant innovation potential. This paper provides a comprehensive review of existing mechanisms, categorizing resource provisioning approaches into static, dynamic, and user-centric models, while examining applications across domains such as IoT, healthcare, and autonomous systems. The survey highlights challenges such as scalability, interoperability, and security in managing dynamic and heterogeneous infrastructures. More >

  • Open Access

    REVIEW

    MediGuard: A Survey on Security Attacks in Blockchain-IoT Ecosystems for e-Healthcare Applications

    Shrabani Sutradhar1,2, Rajesh Bose3, Sudipta Majumder1, Arfat Ahmad Khan4,*, Sandip Roy3, Fasee Ullah5, Deepak Prashar6,7

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3975-4029, 2025, DOI:10.32604/cmc.2025.061965 - 19 May 2025

    Abstract Cloud-based setups are intertwined with the Internet of Things and advanced, and technologies such as blockchain revolutionize conventional healthcare infrastructure. This digitization has major advantages, mainly enhancing the security barriers of the green tree infrastructure. In this study, we conducted a systematic review of over 150 articles that focused exclusively on blockchain-based healthcare systems, security vulnerabilities, cyberattacks, and system limitations. In addition, we considered several solutions proposed by thousands of researchers worldwide. Our results mostly delineate sustained threats and security concerns in blockchain-based medical health infrastructures for data management, transmission, and processing. Here, we describe… More >

  • Open Access

    ARTICLE

    CloudViT: A Lightweight Ground-Based Cloud Image Classification Model with the Ability to Capture Global Features

    Daoming Wei1, Fangyan Ge2, Bopeng Zhang1, Zhiqiang Zhao3, Dequan Li3,*, Lizong Xi4, Jinrong Hu5,*, Xin Wang6

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5729-5746, 2025, DOI:10.32604/cmc.2025.061402 - 19 May 2025

    Abstract Accurate cloud classification plays a crucial role in aviation safety, climate monitoring, and localized weather forecasting. Current research has been focusing on machine learning techniques, particularly deep learning based model, for the types identification. However, traditional approaches such as convolutional neural networks (CNNs) encounter difficulties in capturing global contextual information. In addition, they are computationally expensive, which restricts their usability in resource-limited environments. To tackle these issues, we present the Cloud Vision Transformer (CloudViT), a lightweight model that integrates CNNs with Transformers. The integration enables an effective balance between local and global feature extraction. To… More >

  • Open Access

    ARTICLE

    Bidirectional LSTM-Based Energy Consumption Forecasting: Advancing AI-Driven Cloud Integration for Cognitive City Energy Management

    Sheik Mohideen Shah1, Meganathan Selvamani1, Mahesh Thyluru Ramakrishna2,*, Surbhi Bhatia Khan3,4,5, Shakila Basheer6, Wajdan Al Malwi7, Mohammad Tabrez Quasim8

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2907-2926, 2025, DOI:10.32604/cmc.2025.063809 - 16 April 2025

    Abstract Efficient energy management is a cornerstone of advancing cognitive cities, where AI, IoT, and cloud computing seamlessly integrate to meet escalating global energy demands. Within this context, the ability to forecast electricity consumption with precision is vital, particularly in residential settings where usage patterns are highly variable and complex. This study presents an innovative approach to energy consumption forecasting using a bidirectional Long Short-Term Memory (LSTM) network. Leveraging a dataset containing over two million multivariate, time-series observations collected from a single household over nearly four years, our model addresses the limitations of traditional time-series forecasting… More >

  • Open Access

    ARTICLE

    A Category-Agnostic Hybrid Contrastive Learning Method for Few-Shot Point Cloud Object Detection

    Xuejing Li*

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1667-1681, 2025, DOI:10.32604/cmc.2025.062161 - 16 April 2025

    Abstract Few-shot point cloud 3D object detection (FS3D) aims to identify and locate objects of novel classes within point clouds using knowledge acquired from annotated base classes and a minimal number of samples from the novel classes. Due to imbalanced training data, existing FS3D methods based on fully supervised learning can lead to overfitting toward base classes, which impairs the network’s ability to generalize knowledge learned from base classes to novel classes and also prevents the network from extracting distinctive foreground and background representations for novel class objects. To address these issues, this thesis proposes a… More >

  • Open Access

    ARTICLE

    Provable Data Possession with Outsourced Tag Generation for AI-Driven E-Commerce

    Yi Li1, Wenying Zheng2, Yu-Sheng Su3,4,5,*, Meiqin Tang6

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2719-2734, 2025, DOI:10.32604/cmc.2025.059949 - 16 April 2025

    Abstract AI applications have become ubiquitous, bringing significant convenience to various industries. In e-commerce, AI can enhance product recommendations for individuals and provide businesses with more accurate predictions for market strategy development. However, if the data used for AI applications is damaged or lost, it will inevitably affect the effectiveness of these AI applications. Therefore, it is essential to verify the integrity of e-commerce data. Although existing Provable Data Possession (PDP) protocols can verify the integrity of cloud data, they are not suitable for e-commerce scenarios due to the limited computational capabilities of edge servers, which More >

  • Open Access

    ARTICLE

    Advancing Railway Infrastructure Monitoring: A Case Study on Railway Pole Detection

    Yuxin Yan, Huirui Wang, Jingyi Wen, Zerong Lan, Liang Wang*

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3059-3073, 2025, DOI:10.32604/cmc.2024.057949 - 16 April 2025

    Abstract The development of artificial intelligence (AI) technologies creates a great chance for the iteration of railway monitoring. This paper proposes a comprehensive method for railway utility pole detection. The framework of this paper on railway systems consists of two parts: point cloud preprocessing and railway utility pole detection. This method overcomes the challenges of dynamic environment adaptability, reliance on lighting conditions, sensitivity to weather and environmental conditions, and visual occlusion issues present in 2D images and videos, which utilize mobile LiDAR (Laser Radar) acquisition devices to obtain point cloud data. Due to factors such as… More >

  • Open Access

    ARTICLE

    An Efficient and Secure Data Audit Scheme for Cloud-Based EHRs with Recoverable and Batch Auditing

    Yuanhang Zhang1, Xu An Wang1,2,*, Weiwei Jiang3, Mingyu Zhou1, Xiaoxuan Xu1, Hao Liu1

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1533-1553, 2025, DOI:10.32604/cmc.2025.062910 - 26 March 2025

    Abstract Cloud storage, a core component of cloud computing, plays a vital role in the storage and management of data. Electronic Health Records (EHRs), which document users’ health information, are typically stored on cloud servers. However, users’ sensitive data would then become unregulated. In the event of data loss, cloud storage providers might conceal the fact that data has been compromised to protect their reputation and mitigate losses. Ensuring the integrity of data stored in the cloud remains a pressing issue that urgently needs to be addressed. In this paper, we propose a data auditing scheme… More >

  • Open Access

    ARTICLE

    Fine-Grained Point Cloud Intensity Correction Modeling Method Based on Mobile Laser Scanning

    Xu Liu1, Qiujie Li1,*, Youlin Xu1, Musaed Alhussein2, Khursheed Aurangzeb2,*, Fa Zhu1

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 575-593, 2025, DOI:10.32604/cmc.2025.062445 - 26 March 2025

    Abstract The correction of Light Detection and Ranging (LiDAR) intensity data is of great significance for enhancing its application value. However, traditional intensity correction methods based on Terrestrial Laser Scanning (TLS) technology rely on manual site setup to collect intensity training data at different distances and incidence angles, which is noisy and limited in sample quantity, restricting the improvement of model accuracy. To overcome this limitation, this study proposes a fine-grained intensity correction modeling method based on Mobile Laser Scanning (MLS) technology. The method utilizes the continuous scanning characteristics of MLS technology to obtain dense point… More >

  • Open Access

    ARTICLE

    Enhanced Triple Layered Approach for Mitigating Security Risks in Cloud

    Tajinder Kumar1, Purushottam Sharma2,*, Xiaochun Cheng3,*, Sachin Lalar4, Shubham Kumar5, Sandhya Bansal6

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 719-738, 2025, DOI:10.32604/cmc.2025.060836 - 26 March 2025

    Abstract With cloud computing, large chunks of data can be handled at a small cost. However, there are some reservations regarding the security and privacy of cloud data stored. For solving these issues and enhancing cloud computing security, this research provides a Three-Layered Security Access model (TLSA) aligned to an intrusion detection mechanism, access control mechanism, and data encryption system. The TLSA underlines the need for the protection of sensitive data. This proposed approach starts with Layer 1 data encryption using the Advanced Encryption Standard (AES). For data transfer and storage, this encryption guarantees the data’s… More >

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