Finding effective solutions to accomplish quick and efficient resource allocation is a challenging task in the area of resource management in Cloud Data Services. Presently, a large portion of existing methodologies focus only on finding out the suitable ways to map each specific resource request to appropriate servers. These approaches become complex when the resource allocation issue increments with the size of data centre and could not achieve fast as well as efficient resource allocation for large scale data centres. Resource allocation is a complex process and if not handled properly may lead to contention, scarcity, over or under provisioning of available hardware and software resources. To overcome these drawbacks a hybrid algorithm called as Flower Pollination and Fruit Fly Optimization Algorithm (Hybrid FPFA) is proposed in this research. In resource allocation process, FPFA predicts the required number of physical machines under the predefined virtual machine allocation delay constraint. The performances of multi resource allocation in terms of different evaluation metrics were analyzed and the proposed approach has yielded better outcomes.


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    Titel :

    Hybrid FPFA based multi resources allocation in cloud computing


    Beteiligte:

    Kongress:

    5TH INTERNATIONAL CONFERENCE ON INNOVATIVE DESIGN, ANALYSIS & DEVELOPMENT PRACTICES IN AEROSPACE & AUTOMOTIVE ENGINEERING: I-DAD’22 ; 2022 ; Chennai, India


    Erschienen in:

    Erscheinungsdatum :

    07.06.2023


    Format / Umfang :

    24 pages





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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