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  • Open Access

    REVIEW

    Systematic Review: Load Balancing in Cloud Computing by Using Metaheuristic Based Dynamic Algorithms

    Darakhshan Syed*, Ghulam Muhammad, Safdar Rizvi

    Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 437-476, 2024, DOI:10.32604/iasc.2024.050681 - 11 July 2024

    Abstract Cloud Computing has the ability to provide on-demand access to a shared resource pool. It has completely changed the way businesses are managed, implement applications, and provide services. The rise in popularity has led to a significant increase in the user demand for services. However, in cloud environments efficient load balancing is essential to ensure optimal performance and resource utilization. This systematic review targets a detailed description of load balancing techniques including static and dynamic load balancing algorithms. Specifically, metaheuristic-based dynamic load balancing algorithms are identified as the optimal solution in case of increased traffic. More >

  • Open Access

    ARTICLE

    Distributed Graph Database Load Balancing Method Based on Deep Reinforcement Learning

    Shuming Sha1,2, Naiwang Guo3, Wang Luo1,2, Yong Zhang1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5105-5124, 2024, DOI:10.32604/cmc.2024.049584 - 20 June 2024

    Abstract This paper focuses on the scheduling problem of workflow tasks that exhibit interdependencies. Unlike independent batch tasks, workflows typically consist of multiple subtasks with intrinsic correlations and dependencies. It necessitates the distribution of various computational tasks to appropriate computing node resources in accordance with task dependencies to ensure the smooth completion of the entire workflow. Workflow scheduling must consider an array of factors, including task dependencies, availability of computational resources, and the schedulability of tasks. Therefore, this paper delves into the distributed graph database workflow task scheduling problem and proposes a workflow scheduling methodology based… More >

  • Open Access

    ARTICLE

    Hybrid Hierarchical Particle Swarm Optimization with Evolutionary Artificial Bee Colony Algorithm for Task Scheduling in Cloud Computing

    Shasha Zhao1,2,3,*, Huanwen Yan1,2, Qifeng Lin1,2, Xiangnan Feng1,2, He Chen1,2, Dengyin Zhang1,2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1135-1156, 2024, DOI:10.32604/cmc.2024.045660 - 30 January 2024

    Abstract Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing environment. Short execution time and low load imbalance may be the challenges for some algorithms in resource scheduling scenarios. In this work, the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm (HPSO-EABC) has been proposed, which hybrids our presented Evolutionary Artificial Bee Colony (EABC), and Hierarchical Particle Swarm Optimization (HPSO) algorithm. The HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC algorithm. Comprehensive testing including evaluations of algorithm convergence speed,… More >

  • Open Access

    ARTICLE

    A Multi-Objective Genetic Algorithm Based Load Balancing Strategy for Health Monitoring Systems in Fog-Cloud

    Hayder Makki Shakir, Jaber Karimpour*, Jafar Razmara

    Computer Systems Science and Engineering, Vol.48, No.1, pp. 35-55, 2024, DOI:10.32604/csse.2023.038545 - 26 January 2024

    Abstract As the volume of data and data-generating equipment in healthcare settings grows, so do issues like latency and inefficient processing inside health monitoring systems. The Internet of Things (IoT) has been used to create a wide variety of health monitoring systems. Most modern health monitoring solutions are based on cloud computing. However, large-scale deployment of latency-sensitive healthcare applications is hampered by the cloud’s design, which introduces significant delays during the processing of vast data volumes. By strategically positioning servers close to end users, fog computing mitigates latency issues and dramatically improves scaling on demand, resource… More >

  • Open Access

    ARTICLE

    Cross-Domain Authentication Scheme Based on Blockchain and Consistent Hash Algorithm for System-Wide Information Management

    Lizhe Zhang1,2,*, Yongqiang Huang2, Jia Nie2, Kenian Wang1,2

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1467-1488, 2023, DOI:10.32604/cmc.2023.042305 - 29 November 2023

    Abstract System-wide information management (SWIM) is a complex distributed information transfer and sharing system for the next generation of Air Transportation System (ATS). In response to the growing volume of civil aviation air operations, users accessing different authentication domains in the SWIM system have problems with the validity, security, and privacy of SWIM-shared data. In order to solve these problems, this paper proposes a SWIM cross-domain authentication scheme based on a consistent hashing algorithm on consortium blockchain and designs a blockchain certificate format for SWIM cross-domain authentication. The scheme uses a consistent hash algorithm with virtual… More >

  • Open Access

    ARTICLE

    A Trusted Edge Resource Allocation Framework for Internet of Vehicles

    Yuxuan Zhong1, Siya Xu1, Boxian Liao1, Jizhao Lu2, Huiping Meng2, Zhili Wang1, Xingyu Chen1,*, Qinghan Li3

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2629-2644, 2023, DOI:10.32604/cmc.2023.035526 - 29 November 2023

    Abstract With the continuous progress of information technique, assisted driving technology has become an effective technique to avoid traffic accidents. Due to the complex road conditions and the threat of vehicle information being attacked and tampered with, it is difficult to ensure information security. This paper uses blockchain to ensure the safety of driving information and introduces mobile edge computing technology to monitor vehicle information and road condition information in real time, calculate the appropriate speed, and plan a reasonable driving route for the driver. To solve these problems, this paper proposes a trusted edge resource… More >

  • Open Access

    ARTICLE

    Efficient Cloud Resource Scheduling with an Optimized Throttled Load Balancing Approach

    V. Dhilip Kumar1, J. Praveenchandar2, Muhammad Arif3,*, Adrian Brezulianu4, Oana Geman5, Atif Ikram3,6

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2179-2188, 2023, DOI:10.32604/cmc.2023.034764 - 29 November 2023

    Abstract Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage, processing power, and other computer system resources. It is also referred to as a system that will let the consumers utilize computational resources like databases, servers, storage, and intelligence over the Internet. In a cloud network, load balancing is the process of dividing network traffic among a cluster of available servers to increase efficiency. It is also known as a server pool or server farm. When a single node is overwhelmed, balancing the workload is needed to manage unpredictable workflows. The More >

  • Open Access

    ARTICLE

    A Multilevel Hierarchical Parallel Algorithm for Large-Scale Finite Element Modal Analysis

    Gaoyuan Yu1, Yunfeng Lou2, Hang Dong3, Junjie Li1, Xianlong Jin1,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2795-2816, 2023, DOI:10.32604/cmc.2023.037375 - 08 October 2023

    Abstract The strict and high-standard requirements for the safety and stability of major engineering systems make it a tough challenge for large-scale finite element modal analysis. At the same time, realizing the systematic analysis of the entire large structure of these engineering systems is extremely meaningful in practice. This article proposes a multilevel hierarchical parallel algorithm for large-scale finite element modal analysis to reduce the parallel computational efficiency loss when using heterogeneous multicore distributed storage computers in solving large-scale finite element modal analysis. Based on two-level partitioning and four-transformation strategies, the proposed algorithm not only improves… More >

  • Open Access

    ARTICLE

    Machine Learning-Enabled Communication Approach for the Internet of Medical Things

    Rahim Khan1,3, Abdullah Ghani1, Samia Allaoua Chelloug2,*, Mohammed Amin4, Aamir Saeed5, Jason Teo1

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1569-1584, 2023, DOI:10.32604/cmc.2023.039859 - 30 August 2023

    Abstract The Internet of Medical Things (IoMT) is mainly concerned with the efficient utilisation of wearable devices in the healthcare domain to manage various processes automatically, whereas machine learning approaches enable these smart systems to make informed decisions. Generally, broadcasting is used for the transmission of frames, whereas congestion, energy efficiency, and excessive load are among the common issues associated with existing approaches. In this paper, a machine learning-enabled shortest path identification scheme is presented to ensure reliable transmission of frames, especially with the minimum possible communication overheads in the IoMT network. For this purpose, the… More >

  • Open Access

    ARTICLE

    Survey of Resources Allocation Techniques with a Quality of Service (QoS) Aware in a Fog Computing Environment

    Wan Norsyafizan W. Muhamad1, Kaharudin Dimyati2, Muhammad Awais Javed3, Suzi Seroja Sarnin1,*, Divine Senanu Ametefe1

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1291-1308, 2023, DOI:10.32604/cmc.2023.037214 - 08 June 2023

    Abstract The tremendous advancement in distributed computing and Internet of Things (IoT) applications has resulted in the adoption of fog computing as today’s widely used framework complementing cloud computing. Thus, suitable and effective applications could be performed to satisfy the applications’ latency requirement. Resource allocation techniques are essential aspects of fog networks which prevent unbalanced load distribution. Effective resource management techniques can improve the quality of service metrics. Due to the limited and heterogeneous resources available within the fog infrastructure, the fog layer’s resources need to be optimised to efficiently manage and distribute them to different… More >

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