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  • Open Access

    ARTICLE

    Electromechanical Transient Modeling Analysis of Large-Scale New Energy Grid Connection

    Shichao Cao*, Yonggang Dong, Xiaoying Liu

    Energy Engineering, Vol.121, No.4, pp. 1109-1125, 2024, DOI:10.32604/ee.2023.043004

    Abstract The synchronous virtual machine uses inverter power to imitate the performance of the conventional synchronous machine. It also has the same inertia, damping, frequency, voltage regulation, and other external performance as the generator. It is the key technology to realize new energy grid connections’ stable and reliable operation. This project studies a dynamic simulation model of an extensive new energy power system based on the virtual synchronous motor. A new energy storage method is proposed. The mathematical energy storage model is established by combining the fixed rotor model of a synchronous virtual machine with the charge-discharge power, state of charge,… More >

  • Open Access

    ARTICLE

    Virtual Machine Consolidation with Multi-Step Prediction and Affinity-Aware Technique for Energy-Efficient Cloud Data Centers

    Pingping Li*, Jiuxin Cao

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 81-105, 2023, DOI:10.32604/cmc.2023.039076

    Abstract Virtual machine (VM) consolidation is an effective way to improve resource utilization and reduce energy consumption in cloud data centers. Most existing studies have considered VM consolidation as a bin-packing problem, but the current schemes commonly ignore the long-term relationship between VMs and hosts. In addition, there is a lack of long-term consideration for resource optimization in the VM consolidation, which results in unnecessary VM migration and increased energy consumption. To address these limitations, a VM consolidation method based on multi-step prediction and affinity-aware technique for energy-efficient cloud data centers (MPaAFVMC) is proposed. The proposed method uses an improved linear… More >

  • Open Access

    ARTICLE

    Performance Framework for Virtual Machine Migration in Cloud Computing

    Tahir Alyas1, Taher M. Ghazal2,3, Badria Sulaiman Alfurhood4, Munir Ahmad5, Ossma Ali Thawabeh6, Khalid Alissa7, Qaiser Abbas8,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6289-6305, 2023, DOI:10.32604/cmc.2023.035161

    Abstract In the cloud environment, the transfer of data from one cloud server to another cloud server is called migration. Data can be delivered in various ways, from one data centre to another. This research aims to increase the migration performance of the virtual machine (VM) in the cloud environment. VMs allow cloud customers to store essential data and resources. However, server usage has grown dramatically due to the virtualization of computer systems, resulting in higher data centre power consumption, storage needs, and operating expenses. Multiple VMs on one data centre manage share resources like central processing unit (CPU) cache, network… More >

  • Open Access

    ARTICLE

    Improved Metaheuristic Based Failure Prediction with Migration Optimization in Cloud Environment

    K. Karthikeyan1,*, Liyakathunisa2, Eman Aljohani2, Thavavel Vaiyapuri3

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1641-1654, 2023, DOI:10.32604/csse.2023.031582

    Abstract Cloud data centers consume high volume of energy for processing and switching the servers among different modes. Virtual Machine (VM) migration enhances the performance of cloud servers in terms of energy efficiency, internal failures and availability. On the other end, energy utilization can be minimized by decreasing the number of active, underutilized sources which conversely reduces the dependability of the system. In VM migration process, the VMs are migrated from underutilized physical resources to other resources to minimize energy utilization and optimize the operations. In this view, the current study develops an Improved Metaheuristic Based Failure Prediction with Virtual Machine… More >

  • Open Access

    ARTICLE

    Adaptive Partial Task Offloading and Virtual Resource Placement in SDN/NFV-Based Network Softwarization

    Prohim Tam1, Sa Math1, Seokhoon Kim1,2,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2141-2154, 2023, DOI:10.32604/csse.2023.030984

    Abstract Edge intelligence brings the deployment of applied deep learning (DL) models in edge computing systems to alleviate the core backbone network congestions. The setup of programmable software-defined networking (SDN) control and elastic virtual computing resources within network functions virtualization (NFV) are cooperative for enhancing the applicability of intelligent edge softwarization. To offer advancement for multi-dimensional model task offloading in edge networks with SDN/NFV-based control softwarization, this study proposes a DL mechanism to recommend the optimal edge node selection with primary features of congestion windows, link delays, and allocatable bandwidth capacities. Adaptive partial task offloading policy considered the DL-based recommendation to… More >

  • Open Access

    ARTICLE

    A Service Level Agreement Aware Online Algorithm for Virtual Machine Migration

    Iftikhar Ahmad1,*, Ambreen Shahnaz2, Muhammad Asfand-e-Yar3, Wajeeha Khalil1, Yasmin Bano1

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 279-291, 2023, DOI:10.32604/cmc.2023.031344

    Abstract The demand for cloud computing has increased manifold in the recent past. More specifically, on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing needs. The cloud service provider fulfills different user requirements using virtualization - where a single physical machine can host multiple Virtual Machines. Each virtual machine potentially represents a different user environment such as operating system, programming environment, and applications. However, these cloud services use a large amount of electrical energy and produce greenhouse gases. To reduce the electricity cost and greenhouse gases, energy efficient algorithms must be… More >

  • Open Access

    ARTICLE

    Tasks Scheduling in Cloud Environment Using PSO-BATS with MLRHE

    Anwar R Shaheen*, Sundar Santhosh Kumar

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2963-2978, 2023, DOI:10.32604/iasc.2023.025780

    Abstract Cloud computing plays a significant role in Information Technology (IT) industry to deliver scalable resources as a service. One of the most important factor to increase the performance of the cloud server is maximizing the resource utilization in task scheduling. The main advantage of this scheduling is to maximize the performance and minimize the time loss. Various researchers examined numerous scheduling methods to achieve Quality of Service (QoS) and to reduce execution time. However, it had disadvantages in terms of low throughput and high response time. Hence, this study aimed to schedule the task efficiently and to eliminate the faults… More >

  • Open Access

    ARTICLE

    Aging Analysis Framework of Windows-Based Systems through Differential-Analysis of System Snapshots

    Eun-Tae Jang1, Sung Hoon Baek2, Ki-Woong Park1,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5091-5102, 2022, DOI:10.32604/cmc.2022.026663

    Abstract When a Windows-based system is used for an exceedingly long time, its performance degrades, and the error occurrence rate tends to increase. This is generally called system aging. To investigate the reasons for system aging, various studies have been conducted within the range of the operating system kernel to the user application. However, finding an accurate reason for system performance degradation remains challenging research topic. In this study, system monitoring was conducted by dividing a system into ‘before software installation,’ ‘after software installation,’ and ‘after software removal.’ We confirmed that when a software installed in a system is removed, various… More >

  • Open Access

    ARTICLE

    Randomized MILP framework for Securing Virtual Machines from Malware Attacks

    R. Mangalagowri1,*, Revathi Venkataraman2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1565-1580, 2023, DOI:10.32604/iasc.2023.026360

    Abstract Cloud computing involves remote server deployments with public network infrastructures that allow clients to access computational resources. Virtual Machines (VMs) are supplied on requests and launched without interactions from service providers. Intruders can target these servers and establish malicious connections on VMs for carrying out attacks on other clustered VMs. The existing system has issues with execution time and false-positive rates. Hence, the overall system performance is degraded considerably. The proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server’s position so that the opponent cannot track the target server beyond a certain point.… More >

  • Open Access

    ARTICLE

    An Asset-Based Approach to Mitigate Zero-Day Ransomware Attacks

    Farag Azzedin*, Husam Suwad, Md Mahfuzur Rahman

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3003-3020, 2022, DOI:10.32604/cmc.2022.028646

    Abstract This article presents an asset-based security system where security practitioners build their systems based on information they own and not solicited by observing attackers’ behavior. Current security solutions rely on information coming from attackers. Examples are current monitoring and detection security solutions such as intrusion prevention/detection systems and firewalls. This article envisions creating an imbalance between attackers and defenders in favor of defenders. As such, we are proposing to flip the security game such that it will be led by defenders and not attackers. We are proposing a security system that does not observe the behavior of the attack. On… More >

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