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  • Open Access

    ARTICLE

    An Efficient Computational Method for Differential Equations of Fractional Type

    Mustafa Turkyilmazoglu1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.1, pp. 47-65, 2022, DOI:10.32604/cmes.2022.020781 - 18 July 2022

    Abstract An effective solution method of fractional ordinary and partial differential equations is proposed in the present paper. The standard Adomian Decomposition Method (ADM) is modified via introducing a functional term involving both a variable and a parameter. A residual approach is then adopted to identify the optimal value of the embedded parameter within the frame of L2 norm. Numerical experiments on sample problems of open literature prove that the presented algorithm is quite accurate, more advantageous over the traditional ADM and straightforward to implement for the fractional ordinary and partial differential equations of the recent focus More >

  • Open Access

    ARTICLE

    Optimal Data Placement and Replication Approach for SIoT with Edge

    B. Prabhu Shankar1,*, S. Chitra2

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 661-676, 2022, DOI:10.32604/csse.2022.019507 - 25 October 2021

    Abstract Social networks (SNs) are sources with extreme number of users around the world who are all sharing data like images, audio, and video to their friends using IoT devices. This concept is the so-called Social Internet of Things (SIot). The evolving nature of edge-cloud computing has enabled storage of a large volume of data from various sources, and this task demands an efficient storage procedure. For this kind of large volume of data storage, the usage of data replication using edge with geo-distributed cloud service area is suited to fulfill the user’s expectations with low… More >

  • Open Access

    ARTICLE

    Core – An Optimal Data Placement Strategy in Hadoop for Data Intentitive Applications Based on Cohesion Relation

    Vengadeswaran, Balasundaram

    Computer Systems Science and Engineering, Vol.34, No.1, pp. 47-60, 2019, DOI:10.32604/csse.2019.34.047

    Abstract The tremendous growth of data being generated today is making storage and computing a mammoth task. With its distributed processing capability Hadoop gives an efficient solution for such large data. Hadoop’s default data placement strategy places the data blocks randomly across the nodes without considering the execution parameters resulting in several lacunas such as increased execution time, query latency etc., Also, most of the data required for a task execution may not be locally available which creates data-locality problem. Hence we propose an innovative data placement strategy based on dependency of data blocks across the More >

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