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Search Results (16)
  • Open Access

    ARTICLE

    AI-Driven Resource and Communication-Aware Virtual Machine Placement Using Multi-Objective Swarm Optimization for Enhanced Efficiency in Cloud-Based Smart Manufacturing

    Praveena Nuthakki1, Pavan Kumar T.1, Musaed Alhussein2, Muhammad Shahid Anwar3,*, Khursheed Aurangzeb2, Leenendra Chowdary Gunnam4

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4743-4756, 2024, DOI:10.32604/cmc.2024.058266 - 19 December 2024

    Abstract Cloud computing has emerged as a vital platform for processing resource-intensive workloads in smart manufacturing environments, enabling scalable and flexible access to remote data centers over the internet. In these environments, Virtual Machines (VMs) are employed to manage workloads, with their optimal placement on Physical Machines (PMs) being crucial for maximizing resource utilization. However, achieving high resource utilization in cloud data centers remains a challenge due to multiple conflicting objectives, particularly in scenarios involving inter-VM communication dependencies, which are common in smart manufacturing applications. This manuscript presents an AI-driven approach utilizing a modified Multi-Objective Particle More >

  • Open Access

    ARTICLE

    AMAD: Adaptive Mapping Approach for Datacenter Networks, an Energy-Friend Resource Allocation Framework via Repeated Leader Follower Game

    Ahmad Nahar Quttoum1,*, Muteb Alshammari2

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4577-4601, 2024, DOI:10.32604/cmc.2024.054102 - 12 September 2024

    Abstract Cloud Datacenter Network (CDN) providers usually have the option to scale their network structures to allow for far more resource capacities, though such scaling options may come with exponential costs that contradict their utility objectives. Yet, besides the cost of the physical assets and network resources, such scaling may also impose more loads on the electricity power grids to feed the added nodes with the required energy to run and cool, which comes with extra costs too. Thus, those CDN providers who utilize their resources better can certainly afford their services at lower price-units when… More >

  • Open Access

    ARTICLE

    Reinforcement Effect of Recycled CFRP on Cement-Based Composites: With a Comparison to Commercial Carbon Fiber Powder

    Hantao Huang, Zhifang Zhang*, Zhenhua Wu, Yao Liu

    Structural Durability & Health Monitoring, Vol.18, No.4, pp. 409-423, 2024, DOI:10.32604/sdhm.2024.048597 - 05 June 2024

    Abstract In this paper, recycled carbon fiber reinforced polymer (CFRP) mixture (CFRP-M, including recycled carbon fiber and powder) and refined recycled CFRP fiber (CFRP-F, mostly recycled carbon fiber) were added to cement to study the influence of addition on the flexural strength, compressive strength, and fluidity of cement-based materials. The recycled CFRP were prepared by mechanically processing the prepreg scraps generated during the manufacture of CFRP products. For comparison, commercial carbon fiber powder was also added in cement and the performance was compared to that of addition of recycled CFRP. The hydration products and strengthening mechanism… More >

  • Open Access

    REVIEW

    A Systematic Literature Review on Task Allocation and Performance Management Techniques in Cloud Data Center

    Nidhika Chauhan1, Navneet Kaur2, Kamaljit Singh Saini2, Sahil Verma3, Abdulatif Alabdulatif4, Ruba Abu Khurma5,7, Maribel Garcia-Arenas6, Pedro A. Castillo6,*

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 571-608, 2024, DOI:10.32604/csse.2024.042690 - 20 May 2024

    Abstract As cloud computing usage grows, cloud data centers play an increasingly important role. To maximize resource utilization, ensure service quality, and enhance system performance, it is crucial to allocate tasks and manage performance effectively. The purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data centers. The aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies, categories, and gaps. A literature review was conducted, which included the analysis of 463 task allocations and 480 performance management papers. The… More >

  • Open Access

    ARTICLE

    Overbooking-Enabled Task Scheduling and Resource Allocation in Mobile Edge Computing Environments

    Jixun Gao1,2, Bingyi Hu2, Jialei Liu3,4,*, Huaichen Wang5, Quanzhen Huang1, Yuanyuan Zhao6

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1-16, 2023, DOI:10.32604/iasc.2023.036890 - 29 April 2023

    Abstract Mobile Edge Computing (MEC) is proposed to solve the needs of Internet of Things (IoT) users for high resource utilization, high reliability and low latency of service requests. However, the backup virtual machine is idle when its primary virtual machine is running normally, which will waste resources. Overbooking the backup virtual machine under the above circumstances can effectively improve resource utilization. First, these virtual machines are deployed into slots randomly, and then some tasks with cooperative relationship are offloaded to virtual machines for processing. Different deployment locations have different resource utilization and average service response… More >

  • Open Access

    ARTICLE

    Battle Royale Optimization-Based Resource Scheduling Scheme for Cloud Computing Environment

    Lenin Babu Russeliah1,*, R. Adaline Suji2, D. Bright Anand3

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3925-3938, 2023, DOI:10.32604/csse.2023.034727 - 03 April 2023

    Abstract Cloud computing (CC) is developing as a powerful and flexible computational structure for providing ubiquitous service to users. It receives interrelated software and hardware resources in an integrated manner distinct from the classical computational environment. The variation of software and hardware resources were combined and composed as a resource pool. The software no more resided in the single hardware environment, it can be executed on the schedule of resource pools to optimize resource consumption. Optimizing energy consumption in CC environments is the question that allows utilizing several energy conservation approaches for effective resource allocation. This… More >

  • Open Access

    ARTICLE

    An Efficient Framework for Utilizing Underloaded Servers in Compute Cloud

    M. Hema1,*, S. Kanaga Suba Raja2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 143-156, 2023, DOI:10.32604/csse.2023.024895 - 01 June 2022

    Abstract In cloud data centers, the consolidation of workload is one of the phases during which the available hosts are allocated tasks. This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement (SLA). To consolidate the workloads, the hosts are segregated into three categories: normal hosts, under-loaded hosts, and overloaded hosts based on their utilization. It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish. Threshold values were proposed in the literature to detect this scenario.… More >

  • Open Access

    ARTICLE

    An Adaptive Genetic Algorithm-Based Load Balancing-Aware Task Scheduling Technique for Cloud Computing

    Mohit Agarwal1,*, Shikha Gupta2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6103-6119, 2022, DOI:10.32604/cmc.2022.030778 - 28 July 2022

    Abstract Task scheduling in highly elastic and dynamic processing environments such as cloud computing have become the most discussed problem among researchers. Task scheduling algorithms are responsible for the allocation of the tasks among the computing resources for their execution, and an inefficient task scheduling algorithm results in under-or over-utilization of the resources, which in turn leads to degradation of the services. Therefore, in the proposed work, load balancing is considered as an important criterion for task scheduling in a cloud computing environment as it can help in reducing the overhead in the critical decision-oriented process.… More >

  • Open Access

    ARTICLE

    Bayes Theorem Based Virtual Machine Scheduling for Optimal Energy Consumption

    R. Swathy*, B. Vinayagasundaram

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 159-174, 2022, DOI:10.32604/csse.2022.023706 - 23 March 2022

    Abstract This paper proposes an algorithm for scheduling Virtual Machines (VM) with energy saving strategies in the physical servers of cloud data centers. Energy saving strategy along with a solution for productive resource utilization for VM deployment in cloud data centers is modeled by a combination of “Virtual Machine Scheduling using Bayes Theorem” algorithm (VMSBT) and Virtual Machine Migration (VMMIG) algorithm. It is shown that the overall data center’s consumption of energy is minimized with a combination of VMSBT algorithm and Virtual Machine Migration (VMMIG) algorithm. Virtual machine migration between the active physical servers in the… More >

  • Open Access

    ARTICLE

    Metaheuristic Based Resource Scheduling Technique for Distributed Robotic Control Systems

    P. Anandraj1,*, S. Ramabalan2

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 795-811, 2022, DOI:10.32604/csse.2022.022107 - 04 January 2022

    Abstract The design of controllers for robots is a complex system that is to be dealt with several tasks in real time for enabling the robots to function independently. The distributed robotic control system can be used in real time for resolving various challenges such as localization, motion controlling, mapping, route planning, etc. The distributed robotic control system can manage different kinds of heterogenous devices. Designing a distributed robotic control system is a challenging process as it needs to operate effectually under different hardware configurations and varying computational requirements. For instance, scheduling of resources (such as… More >

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