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- W4382808732 abstract "Various services and scalable computing resources are made available via the internet by cloud computing. Cloud reliability has recently grown significantly as a result of features that enable various tenants to share and multiplex computer resources. The stability of cloud services like those based on virtual servers (VS) must be improved in a cloud data center (CDC), though. To guarantee the dependability of virtual servers (VSs) in the (Infrastructure as a Service (IaaS) cloud model, this study suggests two fuzzy inference systems (FIS), referred to as Physical Server FIS1 (PSFIS1) and PSFIS2 for fault tolerance of VSs in CDC. Checkpointing serves as a fault tolerance (FT) process for VSs in the suggested inference systems. These systems assist in choosing the best physical servers (PSs) to use for saving the snapshot of tasks running on the virtual servers (VSs). To compare the suggested FISs in terms of complication, elasticity, and improved PS selection, the projected FIS is implemented in MATLAB. Though the PSFIS1 is less sophisticated than PSFIS2, the PSFIS2 is more elastic and produces an improved selection of PS than PSFIS1, according to simulation results." @default.
- W4382808732 created "2023-07-02" @default.
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- W4382808732 date "2023-01-01" @default.
- W4382808732 modified "2023-10-18" @default.
- W4382808732 title "Checkpoint Snapshot Placement in the Cloud Data Center Using Fuzzy Inference System" @default.
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- W4382808732 doi "https://doi.org/10.1007/978-981-99-0973-5_44" @default.
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