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  • Open Access

    ARTICLE

    GENOME: Genetic Encoding for Novel Optimization of Malware Detection and Classification in Edge Computing

    Sang-Hoon Choi1, Ki-Woong Park2,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4021-4039, 2025, DOI:10.32604/cmc.2025.061267 - 06 March 2025

    Abstract The proliferation of Internet of Things (IoT) devices has established edge computing as a critical paradigm for real-time data analysis and low-latency processing. Nevertheless, the distributed nature of edge computing presents substantial security challenges, rendering it a prominent target for sophisticated malware attacks. Existing signature-based and behavior-based detection methods are ineffective against the swiftly evolving nature of malware threats and are constrained by the availability of resources. This paper suggests the Genetic Encoding for Novel Optimization of Malware Evaluation (GENOME) framework, a novel solution that is intended to improve the performance of malware detection and… More >

  • Open Access

    ARTICLE

    Research on the Optimal Scheduling Model of Energy Storage Plant Based on Edge Computing and Improved Whale Optimization Algorithm

    Zhaoyu Zeng1, Fuyin Ni1,2,*

    Energy Engineering, Vol.122, No.3, pp. 1153-1174, 2025, DOI:10.32604/ee.2025.059568 - 07 March 2025

    Abstract Energy storage power plants are critical in balancing power supply and demand. However, the scheduling of these plants faces significant challenges, including high network transmission costs and inefficient inter-device energy utilization. To tackle these challenges, this study proposes an optimal scheduling model for energy storage power plants based on edge computing and the improved whale optimization algorithm (IWOA). The proposed model designs an edge computing framework, transferring a large share of data processing and storage tasks to the network edge. This architecture effectively reduces transmission costs by minimizing data travel time. In addition, the model… More >

  • Open Access

    ARTICLE

    MATD3-Based End-Edge Collaborative Resource Optimization for NOMA-Assisted Industrial Wireless Networks

    Ru Hao1,2,3, Chi Xu2,3,*, Jing Liu1

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3203-3222, 2025, DOI:10.32604/cmc.2024.059689 - 17 February 2025

    Abstract Non-orthogonal multiple access (NOMA) technology has recently been widely integrated into multi-access edge computing (MEC) to support task offloading in industrial wireless networks (IWNs) with limited radio resources. This paper minimizes the system overhead regarding task processing delay and energy consumption for the IWN with hybrid NOMA and orthogonal multiple access (OMA) schemes. Specifically, we formulate the system overhead minimization (SOM) problem by considering the limited computation and communication resources and NOMA efficiency. To solve the complex mixed-integer nonconvex problem, we combine the multi-agent twin delayed deep deterministic policy gradient (MATD3) and convex optimization, namely More >

  • Open Access

    ARTICLE

    Dynamic Task Offloading Scheme for Edge Computing via Meta-Reinforcement Learning

    Jiajia Liu1,*, Peng Xie2, Wei Li2, Bo Tang2, Jianhua Liu2

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2609-2635, 2025, DOI:10.32604/cmc.2024.058810 - 17 February 2025

    Abstract As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the task offloading strategies by interacting with the entities. In actual application scenarios, users of edge computing are always changing dynamically. However, the existing task offloading strategies cannot be applied to such dynamic scenarios. To solve this problem, we propose a novel dynamic task offloading framework for distributed edge computing, leveraging the potential of meta-reinforcement learning (MRL). Our approach formulates a multi-objective… More >

  • Open Access

    ARTICLE

    Offload Strategy for Edge Computing in Satellite Networks Based on Software Defined Network

    Zhiguo Liu1,#, Yuqing Gui1,#, Lin Wang2,*, Yingru Jiang1

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 863-879, 2025, DOI:10.32604/cmc.2024.057353 - 03 January 2025

    Abstract Satellite edge computing has garnered significant attention from researchers; however, processing a large volume of tasks within multi-node satellite networks still poses considerable challenges. The sharp increase in user demand for latency-sensitive tasks has inevitably led to offloading bottlenecks and insufficient computational capacity on individual satellite edge servers, making it necessary to implement effective task offloading scheduling to enhance user experience. In this paper, we propose a priority-based task scheduling strategy based on a Software-Defined Network (SDN) framework for satellite-terrestrial integrated networks, which clarifies the execution order of tasks based on their priority. Subsequently, we More >

  • Open Access

    ARTICLE

    An Asynchronous Data Transmission Policy for Task Offloading in Edge-Computing Enabled Ultra-Dense IoT

    Dayong Wang1,*, Kamalrulnizam Bin Abu Bakar1, Babangida Isyaku2, Liping Lei3

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4465-4483, 2024, DOI:10.32604/cmc.2024.059616 - 19 December 2024

    Abstract In recent years, task offloading and its scheduling optimization have emerged as widely discussed and significant topics. The multi-objective optimization problems inherent in this domain, particularly those related to resource allocation, have been extensively investigated. However, existing studies predominantly focus on matching suitable computational resources for task offloading requests, often overlooking the optimization of the task data transmission process. This inefficiency in data transmission leads to delays in the arrival of task data at computational nodes within the edge network, resulting in increased service times due to elevated network transmission latencies and idle computational resources.… More >

  • Open Access

    REVIEW

    The Metaverse Review: Exploring the Boundless Ream of Digital Reality

    Shi Dong*, Mengke Liu, Khushnood Abbas

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3451-3498, 2024, DOI:10.32604/cmc.2024.055575 - 19 December 2024

    Abstract The metaverse has emerged as a prominent topic with growing interest fueled by advancements in Web 3.0, blockchain, and immersive technologies. This paper presents a thorough analysis of the metaverse, showcasing its evolution from a conceptual phase rooted in science fiction to a dynamic and transformative digital environment impacting various sectors including gaming, education, healthcare, and entertainment. The paper introduces the metaverse, details its historical development, and introduces key technologies that enable its existence such as virtual and augmented reality, blockchain, and artificial intelligence. Further this work explores diverse application scenarios, future trends, and critical More >

  • Open Access

    ARTICLE

    Computation Offloading in Edge Computing for Internet of Vehicles via Game Theory

    Jianhua Liu*, Jincheng Wei, Rongxin Luo, Guilin Yuan, Jiajia Liu, Xiaoguang Tu

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1337-1361, 2024, DOI:10.32604/cmc.2024.056286 - 15 October 2024

    Abstract With the rapid advancement of Internet of Vehicles (IoV) technology, the demands for real-time navigation, advanced driver-assistance systems (ADAS), vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, and multimedia entertainment systems have made in-vehicle applications increasingly computing-intensive and delay-sensitive. These applications require significant computing resources, which can overwhelm the limited computing capabilities of vehicle terminals despite advancements in computing hardware due to the complexity of tasks, energy consumption, and cost constraints. To address this issue in IoV-based edge computing, particularly in scenarios where available computing resources in vehicles are scarce, a multi-master and multi-slave double-layer game model More >

  • 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 >

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