Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (109)
  • Open Access

    ARTICLE

    Task Offloading and Trajectory Optimization in UAV Networks: A Deep Reinforcement Learning Method Based on SAC and A-Star

    Jianhua Liu*, Peng Xie, Jiajia Liu, Xiaoguang Tu

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1243-1273, 2024, DOI:10.32604/cmes.2024.054002 - 27 September 2024

    Abstract In mobile edge computing, unmanned aerial vehicles (UAVs) equipped with computing servers have emerged as a promising solution due to their exceptional attributes of high mobility, flexibility, rapid deployment, and terrain agnosticism. These attributes enable UAVs to reach designated areas, thereby addressing temporary computing swiftly in scenarios where ground-based servers are overloaded or unavailable. However, the inherent broadcast nature of line-of-sight transmission methods employed by UAVs renders them vulnerable to eavesdropping attacks. Meanwhile, there are often obstacles that affect flight safety in real UAV operation areas, and collisions between UAVs may also occur. To solve… More >

  • Open Access

    ARTICLE

    Blockchain-Based Message Authentication Scheme for Internet of Vehicles in an Edge Computing Environment

    Qiping Zou1, Zhong Ruan2,*, Huaning Song1

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1301-1328, 2024, DOI:10.32604/csse.2024.051796 - 13 September 2024

    Abstract As an important application of intelligent transportation system, Internet of Vehicles (IoV) provides great convenience for users. Users can obtain real-time traffic conditions through the IoV’s services, plan users' travel routes, and improve travel efficiency. However, in the IoV system, there are always malicious vehicle nodes publishing false information. Therefore, it is essential to ensure the legitimacy of the source. In addition, during the peak period of vehicle travel, the vehicle releases a large number of messages, and IoV authentication efficiency is prone to performance bottlenecks. Most existing authentication schemes have the problem of low… More >

  • Open Access

    ARTICLE

    A Probabilistic Trust Model and Control Algorithm to Protect 6G Networks against Malicious Data Injection Attacks in Edge Computing Environments

    Borja Bordel Sánchez1,*, Ramón Alcarria2, Tomás Robles1

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 631-654, 2024, DOI:10.32604/cmes.2024.050349 - 20 August 2024

    Abstract Future 6G communications are envisioned to enable a large catalogue of pioneering applications. These will range from networked Cyber-Physical Systems to edge computing devices, establishing real-time feedback control loops critical for managing Industry 5.0 deployments, digital agriculture systems, and essential infrastructures. The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised. While full automation will enhance industrial efficiency significantly, it concurrently introduces new cyber risks and vulnerabilities. In particular, unattended systems are highly susceptible to trust issues: malicious nodes and false information can be easily introduced into… More >

  • Open Access

    ARTICLE

    A Novel Quantization and Model Compression Approach for Hardware Accelerators in Edge Computing

    Fangzhou He1,3, Ke Ding1,2, Dingjiang Yan3, Jie Li3,*, Jiajun Wang1,2, Mingzhe Chen1,2

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3021-3045, 2024, DOI:10.32604/cmc.2024.053632 - 15 August 2024

    Abstract Massive computational complexity and memory requirement of artificial intelligence models impede their deployability on edge computing devices of the Internet of Things (IoT). While Power-of-Two (PoT) quantization is proposed to improve the efficiency for edge inference of Deep Neural Networks (DNNs), existing PoT schemes require a huge amount of bit-wise manipulation and have large memory overhead, and their efficiency is bounded by the bottleneck of computation latency and memory footprint. To tackle this challenge, we present an efficient inference approach on the basis of PoT quantization and model compression. An integer-only scalar PoT quantization (IOS-PoT)… More >

  • Open Access

    ARTICLE

    Two-Stage IoT Computational Task Offloading Decision-Making in MEC with Request Holding and Dynamic Eviction

    Dayong Wang1,*, Kamalrulnizam Bin Abu Bakar1, Babangida Isyaku2

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2065-2080, 2024, DOI:10.32604/cmc.2024.051944 - 15 August 2024

    Abstract The rapid development of Internet of Things (IoT) technology has led to a significant increase in the computational task load of Terminal Devices (TDs). TDs reduce response latency and energy consumption with the support of task-offloading in Multi-access Edge Computing (MEC). However, existing task-offloading optimization methods typically assume that MEC’s computing resources are unlimited, and there is a lack of research on the optimization of task-offloading when MEC resources are exhausted. In addition, existing solutions only decide whether to accept the offloaded task request based on the single decision result of the current time slot,… More >

  • Open Access

    ARTICLE

    Optimized Binary Neural Networks for Road Anomaly Detection: A TinyML Approach on Edge Devices

    Amna Khatoon1, Weixing Wang1,*, Asad Ullah2, Limin Li3,*, Mengfei Wang1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 527-546, 2024, DOI:10.32604/cmc.2024.051147 - 18 July 2024

    Abstract Integrating Tiny Machine Learning (TinyML) with edge computing in remotely sensed images enhances the capabilities of road anomaly detection on a broader level. Constrained devices efficiently implement a Binary Neural Network (BNN) for road feature extraction, utilizing quantization and compression through a pruning strategy. The modifications resulted in a 28-fold decrease in memory usage and a 25% enhancement in inference speed while only experiencing a 2.5% decrease in accuracy. It showcases its superiority over conventional detection algorithms in different road image scenarios. Although constrained by computer resources and training datasets, our results indicate opportunities for More >

  • Open Access

    ARTICLE

    GCAGA: A Gini Coefficient-Based Optimization Strategy for Computation Offloading in Multi-User-Multi-Edge MEC System

    Junqing Bai1, Qiuchao Dai1,*, Yingying Li2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5083-5103, 2024, DOI:10.32604/cmc.2024.050921 - 20 June 2024

    Abstract To support the explosive growth of Information and Communications Technology (ICT), Mobile Edge Computing (MEC) provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge. However, resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications. To address the difficulty of running computationally intensive applications on resource-constrained clients, a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper. Then a user benefit function EoU (Experience of Users) is… More >

  • Open Access

    ARTICLE

    EG-STC: An Efficient Secure Two-Party Computation Scheme Based on Embedded GPU for Artificial Intelligence Systems

    Zhenjiang Dong1, Xin Ge1, Yuehua Huang1, Jiankuo Dong1, Jiang Xu2,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4021-4044, 2024, DOI:10.32604/cmc.2024.049233 - 20 June 2024

    Abstract This paper presents a comprehensive exploration into the integration of Internet of Things (IoT), big data analysis, cloud computing, and Artificial Intelligence (AI), which has led to an unprecedented era of connectivity. We delve into the emerging trend of machine learning on embedded devices, enabling tasks in resource-limited environments. However, the widespread adoption of machine learning raises significant privacy concerns, necessitating the development of privacy-preserving techniques. One such technique, secure multi-party computation (MPC), allows collaborative computations without exposing private inputs. Despite its potential, complex protocols and communication interactions hinder performance, especially on resource-constrained devices. Efforts… More >

  • Open Access

    ARTICLE

    Proactive Caching at the Wireless Edge: A Novel Predictive User Popularity-Aware Approach

    Yunye Wan1, Peng Chen2, Yunni Xia1,*, Yong Ma3, Dongge Zhu4, Xu Wang5, Hui Liu6, Weiling Li7, Xianhua Niu2, Lei Xu8, Yumin Dong9

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1997-2017, 2024, DOI:10.32604/cmes.2024.048723 - 20 May 2024

    Abstract Mobile Edge Computing (MEC) is a promising technology that provides on-demand computing and efficient storage services as close to end users as possible. In an MEC environment, servers are deployed closer to mobile terminals to exploit storage infrastructure, improve content delivery efficiency, and enhance user experience. However, due to the limited capacity of edge servers, it remains a significant challenge to meet the changing, time-varying, and customized needs for highly diversified content of users. Recently, techniques for caching content at the edge are becoming popular for addressing the above challenges. It is capable of filling… More >

  • Open Access

    ARTICLE

    SCIRD: Revealing Infection of Malicious Software in Edge Computing-Enabled IoT Networks

    Jiehao Ye, Wen Cheng, Xiaolong Liu, Wenyi Zhu, Xuan’ang Wu, Shigen Shen*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2743-2769, 2024, DOI:10.32604/cmc.2024.049985 - 15 May 2024

    Abstract The Internet of Things (IoT) has characteristics such as node mobility, node heterogeneity, link heterogeneity, and topology heterogeneity. In the face of the IoT characteristics and the explosive growth of IoT nodes, which brings about large-scale data processing requirements, edge computing architecture has become an emerging network architecture to support IoT applications due to its ability to provide powerful computing capabilities and good service functions. However, the defense mechanism of Edge Computing-enabled IoT Nodes (ECIoTNs) is still weak due to their limited resources, so that they are susceptible to malicious software spread, which can compromise… More >

Displaying 1-10 on page 1 of 109. Per Page