Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (6)
  • Open Access


    ACO-Inspired Load Balancing Strategy for Cloud-Based Data Centre with Predictive Machine Learning Approach

    Niladri Dey1, T. Gunasekhar1, K. Purnachand2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 513-529, 2023, DOI:10.32604/cmc.2023.035139

    Abstract Virtual Machines are the core of cloud computing and are utilized to get the benefits of cloud computing. Other essential features include portability, recovery after failure, and, most importantly, creating the core mechanism for load balancing. Several study results have been reported in enhancing load-balancing systems employing stochastic or biogenetic optimization methods. It examines the underlying issues with load balancing and the limitations of present load balance genetic optimization approaches. They are criticized for using higher-order probability distributions, more complicated solution search spaces, and adding factors to improve decision-making skills. Thus, this paper explores the possibility of summarizing load characteristics.… More >

  • Open Access


    Hybrid Deep Learning Framework for Privacy Preservation in Geo-Distributed Data Centre

    S. Nithyanantham1,*, G. Singaravel2

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1905-1919, 2022, DOI:10.32604/iasc.2022.022499

    Abstract In recent times, a huge amount of data is being created from different sources and the size of the data generated on the Internet has already surpassed two Exabytes. Big Data processing and analysis can be employed in many disciplines which can aid the decision-making process with privacy preservation of users’ private data. To store large quantity of data, Geo-Distributed Data Centres (GDDC) are developed. In recent times, several applications comprising data analytics and machine learning have been designed for GDDC. In this view, this paper presents a hybrid deep learning framework for privacy preservation in distributed DCs. The proposed… More >

  • Open Access


    Live Migration of Virtual Machines Using a Mamdani Fuzzy Inference System

    Tahir Alyas1, Iqra Javed1, Abdallah Namoun2, Ali Tufail2, Sami Alshmrany2, Nadia Tabassum3,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3019-3033, 2022, DOI:10.32604/cmc.2022.019836

    Abstract Efforts were exerted to enhance the live virtual machines (VMs) migration, including performance improvements of the live migration of services to the cloud. The VMs empower the cloud users to store relevant data and resources. However, the utilization of servers has increased significantly because of the virtualization of computer systems, leading to a rise in power consumption and storage requirements by data centers, and thereby the running costs. Data center migration technologies are used to reduce risk, minimize downtime, and streamline and accelerate the data center move process. Indeed, several parameters, such as non-network overheads and downtime adjustment, may impact… More >

  • Open Access


    Dynamic Automated Infrastructure for Efficient Cloud Data Centre

    R. Dhaya1,*, R. Kanthavel2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1625-1639, 2022, DOI:10.32604/cmc.2022.022213

    Abstract We propose a dynamic automated infrastructure model for the cloud data centre which is aimed as an efficient service stipulation for the enormous number of users. The data center and cloud computing technologies have been at the moment rendering attention to major research and development efforts by companies, governments, and academic and other research institutions. In that, the difficult task is to facilitate the infrastructure to construct the information available to application-driven services and make business-smart decisions. On the other hand, the challenges that remain are the provision of dynamic infrastructure for applications and information anywhere. Further, developing technologies to… More >

  • Open Access


    Energy-Aware Scheduling for Tasks with Target-Time in Blockchain based Data Centres

    I. Devi*, G.R. Karpagam

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 405-419, 2022, DOI:10.32604/csse.2022.018573


    Cloud computing infrastructures have intended to provide computing services to end-users through the internet in a pay-per-use model. The extensive deployment of the Cloud and continuous increment in the capacity and utilization of data centers (DC) leads to massive power consumption. This intensifying scale of DCs has made energy consumption a critical concern. This paper emphasizes the task scheduling algorithm by formulating the system model to minimize the makespan and energy consumption incurred in a data center. Also, an energy-aware task scheduling in the Blockchain-based data center was proposed to offer an optimal solution that minimizes makespan and energy consumption.… More >

  • Open Access


    Secure Information Access Strategy for a Virtual Data Centre

    Sivaranjani Balakrishnan1,∗, D. Surendran2,†

    Computer Systems Science and Engineering, Vol.35, No.5, pp. 357-366, 2020, DOI:10.32604/csse.2020.35.357

    Abstract With the arrival of on-demand computing, data centre requirements are extensive, with fluid boundaries. Loaded Internet applications, service-oriented architectures, virtualization and security provisioning are the major operations of a data centre. Security is an absolute necessity of any network architecture, and the virtual IT data centre is no exception. At the boundary, security is focused on securing the terminals of the data centre from external threats and providing a secure gateway to the Internet. The paradigm shift towards a new computing environment makes communications more complicated for Infrastructure Providers (InP). This complexity includes the security of the data centre’s components… More >

Displaying 1-10 on page 1 of 6. Per Page