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Search Results (7)
  • Open Access

    ARTICLE

    A PSO Improved with Imbalanced Mutation and Task Rescheduling for Task Offloading in End-Edge-Cloud Computing

    Kaili Shao1, Hui Fu1, Ying Song2, Bo Wang3,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2259-2274, 2023, DOI:10.32604/csse.2023.041454

    Abstract To serve various tasks requested by various end devices with different requirements, end-edge-cloud (E2C) has attracted more and more attention from specialists in both academia and industry, by combining both benefits of edge and cloud computing. But nowadays, E2C still suffers from low service quality and resource efficiency, due to the geographical distribution of edge resources and the high dynamic of network topology and user mobility. To address these issues, this paper focuses on task offloading, which makes decisions that which resources are allocated to tasks for their processing. This paper first formulates the problem into binary non-linear programming and… More >

  • Open Access

    ARTICLE

    Edge Cloud Selection in Mobile Edge Computing (MEC)-Aided Applications for Industrial Internet of Things (IIoT) Services

    Dae-Young Kim1, SoYeon Lee2, MinSeung Kim2, Seokhoon Kim1,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2049-2060, 2023, DOI:10.32604/csse.2023.040473

    Abstract In many IIoT architectures, various devices connect to the edge cloud via gateway systems. For data processing, numerous data are delivered to the edge cloud. Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency. There are two types of costs for this kind of IoT network: a communication cost and a computing cost. For service efficiency, the communication cost of data transmission should be minimized, and the computing cost in the edge cloud should be also minimized. Therefore, in this paper, the communication cost for data transmission is defined as the delay factor, and the… More >

  • 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

    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 form a novel hybrid cloud.… More >

  • Open Access

    ARTICLE

    Clustered Single-Board Devices with Docker Container Big Stream Processing Architecture

    N. Penchalaiah1, Abeer S. Al-Humaimeedy2, Mashael Maashi3, J. Chinna Babu4,*, Osamah Ibrahim Khalaf5, Theyazn H. H. Aldhyani6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5349-5365, 2022, DOI:10.32604/cmc.2022.029639

    Abstract The expanding amounts of information created by Internet of Things (IoT) devices places a strain on cloud computing, which is often used for data analysis and storage. This paper investigates a different approach based on edge cloud applications, which involves data filtering and processing before being delivered to a backup cloud environment. This Paper suggest designing and implementing a low cost, low power cluster of Single Board Computers (SBC) for this purpose, reducing the amount of data that must be transmitted elsewhere, using Big Data ideas and technology. An Apache Hadoop and Spark Cluster that was used to run a… More >

  • Open Access

    ARTICLE

    Exploring and Modelling IoT Offloading Policies in Edge Cloud Environments

    Jaber Almutairi1, Mohammad Aldossary2,*

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 611-624, 2022, DOI:10.32604/csse.2022.018112

    Abstract The Internet of Things (IoT) has recently become a popular technology that can play increasingly important roles in every aspect of our daily life. For collaboration between IoT devices and edge cloud servers, edge server nodes provide the computation and storage capabilities for IoT devices through the task offloading process for accelerating tasks with large resource requests. However, the quantitative impact of different offloading architectures and policies on IoT applications’ performance remains far from clear, especially with a dynamic and unpredictable range of connected physical and virtual devices. To this end, this work models the performance impact by exploiting a… More >

  • Open Access

    ARTICLE

    Mobility Management in Small Cell Cluster of Cellular Network

    Adeel Rafiq, Muhammad Afaq, Khizar Abbas, Wang-Cheol Song*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 627-645, 2021, DOI:10.32604/cmc.2021.016529

    Abstract The installation of small cells in a 5G network extends the maximum coverage and provides high availability. However, this approach increases the handover overhead in the Core Network (CN) due to frequent handoffs. The variation of user density and movement inside a region of small cells also increases the handover overhead in CN. However, the present 5G system cannot reduce the handover overhead in CN under such circumstances because it relies on a traditionally rigid and complex hierarchical sequence for a handover procedure. Recently, Not Only Stack (NO Stack) architecture has been introduced for Radio Access Network (RAN) to reduce… More >

  • Open Access

    ARTICLE

    Recent Advances in Mobile Grid and Cloud Computing

    Sayed Chhattan Shah

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 285-298, 2018, DOI:10.1080/10798587.2017.1280995

    Abstract Grid and cloud computing systems have been extensively used to solve large and complex problems in science and engineering fields. These systems include powerful computing resources that are connected through high-speed networks. Due to the recent advances in mobile computing and networking technologies, it has become feasible to integrate various mobile devices, such as robots, aerial vehicles, sensors, and smart phones, with grid and cloud computing systems. This integration enables the design and development of the next generation of applications by sharing of resources in mobile environments and introduces several challenges due to a dynamic and unpredictable network. This paper… More >

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