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  • Open Access

    ARTICLE

    Connected Vehicles Computation Task Offloading Based on Opportunism in Cooperative Edge Computing

    Duan Xue1,2, Yan Guo1,*, Ning Li1, Xiaoxiang Song1

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 609-631, 2023, DOI:10.32604/cmc.2023.035177 - 06 February 2023

    Abstract The traditional multi-access edge computing (MEC) capacity is overwhelmed by the increasing demand for vehicles, leading to acute degradation in task offloading performance. There is a tremendous number of resource-rich and idle mobile connected vehicles (CVs) in the traffic network, and vehicles are created as opportunistic ad-hoc edge clouds to alleviate the resource limitation of MEC by providing opportunistic computing services. On this basis, a novel scalable system framework is proposed in this paper for computation task offloading in opportunistic CV-assisted MEC. In this framework, opportunistic ad-hoc edge cloud and fixed edge cloud cooperate to… More >

  • Open Access

    ARTICLE

    A Dynamic Multi-Attribute Resource Bidding Mechanism with Privacy Protection in Edge Computing

    Shujuan Tian1,2,3, Wenjian Ding1,2,3, Gang Liu4, Yuxia Sun5, Saiqin Long5, Jiang Zhu1,2,3,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 373-391, 2023, DOI:10.32604/cmc.2023.034770 - 06 February 2023

    Abstract In edge computing, a reasonable edge resource bidding mechanism can enable edge providers and users to obtain benefits in a relatively fair fashion. To maximize such benefits, this paper proposes a dynamic multi-attribute resource bidding mechanism (DMRBM). Most of the previous work mainly relies on a third-party agent to exchange information to gain optimal benefits. It is worth noting that when edge providers and users trade with third-party agents which are not entirely reliable and trustworthy, their sensitive information is prone to be leaked. Moreover, the privacy protection of edge providers and users must be… More >

  • Open Access

    ARTICLE

    Task Offloading Based on Vehicular Edge Computing for Autonomous Platooning

    Sanghyuck Nam1, Suhwan Kwak1, Jaehwan Lee2, Sangoh Park1,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 659-670, 2023, DOI:10.32604/csse.2023.034994 - 20 January 2023

    Abstract Autonomous platooning technology is regarded as one of the promising technologies for the future and the research is conducted actively. The autonomous platooning task generally requires highly complex computations so it is difficult to process only with the vehicle’s processing units. To solve this problem, there are many studies on task offloading technique which transfers complex tasks to their neighboring vehicles or computation nodes. However, the existing task offloading techniques which mainly use learning-based algorithms are difficult to respond to the real-time changing road environment due to their complexity. They are also challenging to process… More >

  • Open Access

    REVIEW

    Edge Intelligence with Distributed Processing of DNNs: A Survey

    Sizhe Tang1, Mengmeng Cui1,*, Lianyong Qi2, Xiaolong Xu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 5-42, 2023, DOI:10.32604/cmes.2023.023684 - 05 January 2023

    Abstract With the rapid development of deep learning, the size of data sets and deep neural networks (DNNs) models are also booming. As a result, the intolerable long time for models’ training or inference with conventional strategies can not meet the satisfaction of modern tasks gradually. Moreover, devices stay idle in the scenario of edge computing (EC), which presents a waste of resources since they can share the pressure of the busy devices but they do not. To address the problem, the strategy leveraging distributed processing has been applied to load computation tasks from a single… More >

  • Open Access

    ARTICLE

    Bayes-Q-Learning Algorithm in Edge Computing for Waste Tracking

    D. Palanikkumar1, R. Ramesh Kumar2, Mehedi Masud3, Mrim M. Alnfiai4, Mohamed Abouhawwash5,6,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2425-2440, 2023, DOI:10.32604/iasc.2023.033879 - 05 January 2023

    Abstract The major environmental hazard in this pandemic is the unhygienic disposal of medical waste. Medical wastage is not properly managed it will become a hazard to the environment and humans. Managing medical wastage is a major issue in the city, municipalities in the aspects of the environment, and logistics. An efficient supply chain with edge computing technology is used in managing medical waste. The supply chain operations include processing of waste collection, transportation, and disposal of waste. Many research works have been applied to improve the management of wastage. The main issues in the existing… More >

  • Open Access

    ARTICLE

    DQN-Based Proactive Trajectory Planning of UAVs in Multi-Access Edge Computing

    Adil Khan1,*, Jinling Zhang1, Shabeer Ahmad1, Saifullah Memon2, Babar Hayat1, Ahsan Rafiq3

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4685-4702, 2023, DOI:10.32604/cmc.2023.034892 - 28 December 2022

    Abstract The main aim of future mobile networks is to provide secure, reliable, intelligent, and seamless connectivity. It also enables mobile network operators to ensure their customer’s a better quality of service (QoS). Nowadays, Unmanned Aerial Vehicles (UAVs) are a significant part of the mobile network due to their continuously growing use in various applications. For better coverage, cost-effective, and seamless service connectivity and provisioning, UAVs have emerged as the best choice for telco operators. UAVs can be used as flying base stations, edge servers, and relay nodes in mobile networks. On the other side, Multi-access… More >

  • Open Access

    ARTICLE

    Resource Management in UAV Enabled MEC Networks

    Muhammad Abrar1, Ziyad M. Almohaimeed2,*, Ushna Ajmal1, Rizwan Akram2, Rooha Masroor3, Muhammad Majid Hussain4

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4847-4860, 2023, DOI:10.32604/cmc.2023.030242 - 28 December 2022

    Abstract Mobile edge cloud networks can be used to offload computationally intensive tasks from Internet of Things (IoT) devices to nearby mobile edge servers, thereby lowering energy consumption and response time for ground mobile users or IoT devices. Integration of Unmanned Aerial Vehicles (UAVs) and the mobile edge computing (MEC) server will significantly benefit small, battery-powered, and energy-constrained devices in 5G and future wireless networks. We address the problem of maximising computation efficiency in U-MEC networks by optimising the user association and offloading indicator (OI), the computational capacity (CC), the power consumption, the time duration, and More >

  • Open Access

    ARTICLE

    Transparent Access to Heterogeneous IoT Based on Virtual Resources

    Wenquan Jin1, Sunhwan Lim2, Young-Ho Suh2, Chanwon Park2, Dohyeun Kim3,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4983-4999, 2023, DOI:10.32604/cmc.2023.020851 - 28 December 2022

    Abstract The Internet of Things (IoT) inspires industries to deploy a massive number of connected devices to provide smart and ubiquitous services to influence our daily life. Edge computing leverages sufficient computation and storage at the edge of the network to enable deploying complex functions closer to the environment using Internet-connected devices. According to the purpose of the environment including privacy level, domain functionality, network scale and service quality, various environment-specific services can be provided through heterogeneous applications with sensors and actuators based on edge computing. However, for providing user-friendly service scenarios based on the transparent… More >

  • Open Access

    ARTICLE

    Deep Learning Implemented Visualizing City Cleanliness Level by Garbage Detection

    M. S. Vivekanandan1, T. Jesudas2,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1639-1652, 2023, DOI:10.32604/iasc.2023.032301 - 05 January 2023

    Abstract In an urban city, the daily challenges of managing cleanliness are the primary aspect of routine life, which requires a large number of resources, the manual process of labour, and budget. Street cleaning techniques include street sweepers going away to different metropolitan areas, manually verifying if the street required cleaning taking action. This research presents novel street garbage recognizing robotic navigation techniques by detecting the city’s street-level images and multi-level segmentation. For the large volume of the process, the deep learning-based methods can be better to achieve a high level of classification, object detection, and… More >

  • Open Access

    ARTICLE

    Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks

    Abdelhamied A. Ateya1, Amel Ali Alhussan2,*, Hanaa A. Abdallah3, Mona A. Al duailij2, Abdukodir Khakimov4, Ammar Muthanna5

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1775-1787, 2023, DOI:10.32604/csse.2023.031841 - 03 November 2022

    Abstract Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability, availability, and ultra-low latency. The requirements of such networks are the main challenges that can be handled using a range of recent technologies, including multi-access edge computing (MEC), artificial intelligence (AI), millimeter-wave communications (mmWave), and software-defined networking. Many aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service (QoS). This article considers developing a complex MEC structure for fifth and sixth-generation (5G/6G) cellular networks. Furthermore, More >

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