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  • Open Access


    Exploring High-Performance Architecture for Data Center Networks

    Deshun Li1, Shaorong Sun2, Qisen Wu2, Shuhua Weng1, Yuyin Tan2, Jiangyuan Yao1,*, Xiangdang Huang1, Xingcan Cao3

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 433-443, 2023, DOI:10.32604/csse.2023.034368

    Abstract As a critical infrastructure of cloud computing, data center networks (DCNs) directly determine the service performance of data centers, which provide computing services for various applications such as big data processing and artificial intelligence. However, current architectures of data center networks suffer from a long routing path and a low fault tolerance between source and destination servers, which is hard to satisfy the requirements of high-performance data center networks. Based on dual-port servers and Clos network structure, this paper proposed a novel architecture to construct high-performance data center networks. Logically, the proposed architecture is constructed by inserting a dual-port server… More >

  • Open Access


    Replication Strategy with Comprehensive Data Center Selection Method in Cloud Environments

    M. A. Fazlina, Rohaya Latip*, Hamidah Ibrahim, Azizol Abdullah

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 415-433, 2023, DOI:10.32604/cmc.2023.020764

    Abstract As the amount of data continues to grow rapidly, the variety of data produced by applications is becoming more affluent than ever. Cloud computing is the best technology evolving today to provide multi-services for the mass and variety of data. The cloud computing features are capable of processing, managing, and storing all sorts of data. Although data is stored in many high-end nodes, either in the same data centers or across many data centers in cloud, performance issues are still inevitable. The cloud replication strategy is one of best solutions to address risk of performance degradation in the cloud environment.… More >

  • Open Access


    Load-Aware VM Migration Using Hypergraph Based CDB-LSTM

    N. Venkata Subramanian1, V. S. Shankar Sriram2,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3279-3294, 2023, DOI:10.32604/iasc.2023.023700


    Live Virtual Machine (VM) migration is one of the foremost techniques for progressing Cloud Data Centers’ (CDC) proficiency as it leads to better resource usage. The workload of CDC is often dynamic in nature, it is better to envisage the upcoming workload for early detection of overload status, underload status and to trigger the migration at an appropriate point wherein enough number of resources are available. Though various statistical and machine learning approaches are widely applied for resource usage prediction, they often failed to handle the increase of non-linear CDC data. To overcome this issue, a novel Hypergrah based Convolutional… More >

  • Open Access


    An Eco-Friendly Approach for Reducing Carbon Emissions in Cloud Data Centers

    Mohammad Aldossary1,*, Hatem A. Alharbi2

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3175-3193, 2022, DOI:10.32604/cmc.2022.026041

    Abstract Based on the Saudi Green initiative, which aims to improve the Kingdom's environmental status and reduce the carbon emission of more than 278 million tons by 2030 along with a promising plan to achieve net-zero carbon by 2060, NEOM city has been proposed to be the “Saudi hub” for green energy, since NEOM is estimated to generate up to 120 Gigawatts (GW) of renewable energy by 2030. Nevertheless, the Information and Communication Technology (ICT) sector is considered a key contributor to global energy consumption and carbon emissions. The data centers are estimated to consume about 13% of the overall global… More >

  • Open Access


    Multi-Objective Optimization of Energy Aware Virtual Machine Placement in Cloud Data Center

    B. Gomathi1, B. Saravana Balaji2, V. Krishna Kumar3, Mohamed Abouhawwash4,5,*, Sultan Aljahdali6, Mehedi Masud6, Nina Kuchuk7

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1771-1785, 2022, DOI:10.32604/iasc.2022.024052

    Abstract Cloud computing enables cloud providers to outsource their Information Technology (IT) services from data centers in a pay-as-you-go model. However, Cloud infrastructure comprises virtualized physical resources that consume huge amount of energy and emits carbon footprints to environment. Hence, there should be focus on optimal assignment of Virtual Machines (VM) to Physical Machines (PM) to ensure the energy efficiency and service level performance. In this paper, The Pareto based Multi-Objective Particle Swarm Optimization with Composite Mutation (PSOCM) technique has been proposed to improve the energy efficiency and minimize the Service Level Agreement (SLA) violation in Cloud Environment. In this paper,… More >

  • Open Access


    A Virtual Machine Placement Strategy Based on Virtual Machine Selection and Integration

    Denghui Zhang1,*, Guocai Yin2

    Journal on Internet of Things, Vol.3, No.4, pp. 149-157, 2021, DOI:10.32604/jiot.2021.016936

    Abstract Cloud data centers face the largest energy consumption. In order to save energy consumption in cloud data centers, cloud service providers adopt a virtual machine migration strategy. In this paper, we propose an efficient virtual machine placement strategy (VMP-SI) based on virtual machine selection and integration. Our proposed VMP-SI strategy divides the migration process into three phases: physical host state detection, virtual machine selection and virtual machine placement. The local regression robust (LRR) algorithm and minimum migration time (MMT) policy are individual used in the first and section phase, respectively. Then we design a virtual machine migration strategy that integrates… More >

  • Open Access


    The Use of Single-Phase Immersion Cooling by Using Two Types of Dielectric Fluid for Data Center Energy Savings

    Nugroho Agung Pambudi*, Awibi Muhamad Yusuf, Alfan Sarifudin

    Energy Engineering, Vol.119, No.1, pp. 275-286, 2022, DOI:10.32604/EE.2022.017356

    Abstract Data centers are recognized as one of the most important aspects of the fourth industrial revolution since conventional data centers are inefficient and have dependency on high energy consumption, in which the cooling is responsible for 40% of the usage. Therefore, this research proposes the immersion cooling method to solving the high energy consumption of data centers by cooling its component using two types of dielectric fluids. Four stages of experimental methods are used, such as fluid types, cooling effectiveness, optimization, and durability. Furthermore, benchmark software is used to measure the CPU maximum work with the temperature data performed for… More >

  • Open Access


    Cloud Data Center Selection Using a Modified Differential Evolution

    Yousef Sanjalawe1,2, Mohammed Anbar1,*, Salam Al-E’mari1, Rosni Abdullah1, Iznan Hasbullah1, Mohammed Aladaileh1

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3179-3204, 2021, DOI:10.32604/cmc.2021.018546

    Abstract The interest in selecting an appropriate cloud data center is exponentially increasing due to the popularity and continuous growth of the cloud computing sector. Cloud data center selection challenges are compounded by ever-increasing users’ requests and the number of data centers required to execute these requests. Cloud service broker policy defines cloud data center’s selection, which is a case of an NP-hard problem that needs a precise solution for an efficient and superior solution. Differential evolution algorithm is a metaheuristic algorithm characterized by its speed and robustness, and it is well suited for selecting an appropriate cloud data center. This… More >

  • Open Access


    An Enhanced Decentralized Virtual Machine Migration Approach for Energy-Aware Cloud Data Centers

    R. Jayamala*, A. Valarmathi

    Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 347-358, 2021, DOI:10.32604/iasc.2021.012401

    Abstract Cloud computing is an increasingly important technology to deliver pay-as-you-go online computing services. In this study, the cloud service provider permits the cloud user to pay according to the user’s needs. Various methods have been used to reduce energy utilization in the cloud. The rapid increase of cloud users has led to increased energy consumption and higher operating costs for cloud providers. A key issue in cloud data centers is their massive energy consumption to operate and maintain computing services. Virtual machine (VM) migration is a method to reduce energy consumption. This study proposes enhanced decentralized virtual machine migration (EDVMM),… More >

  • Open Access


    Big Data of Home Energy Management in Cloud Computing

    Rizwan Munir1,*, Yifei Wei1, Rahim Ullah2, Iftikhar Hussain3, Kaleem Arshid4, Umair Tariq1

    Journal of Quantum Computing, Vol.2, No.4, pp. 193-202, 2020, DOI:10.32604/jqc.2020.016151

    Abstract A smart grid is the evolved form of the power grid with the integration of sensing, communication, computing, monitoring, and control technologies. These technologies make the power grid reliable, efficient, and economical. However, the smartness boosts the volume of data in the smart grid. To obligate full benefits, big data has attractive techniques to process and analyze smart grid data. This paper presents and simulates a framework to make sure the use of big data computing technique in the smart grid. The offered framework comprises of the following four layers: (i) Data source layer, (ii) Data transmission layer, (iii) Data… More >

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