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公开(公告)号:US20210105228A1
公开(公告)日:2021-04-08
申请号:US17063627
申请日:2020-10-05
Applicant: Samsung Electronics Co., Ltd.
Inventor: Vimal Bastin Edwin JOSEPH , Karthikeyan SUBRAMANIAM , Parvathi MAHESH HEDATHRI , Peeyus PAL , Karthikeyan NARAYANAN
IPC: H04L12/911 , H04L12/24 , G06K9/62 , G06N5/04
Abstract: This disclosure relates to deployment of additional workload in the NFV-MANO to efficiently utilize resources during a lean workload period of Virtual Network Functions (VNFs) associated with an intelligent cloud platform. The method comprises measuring, over a time period, a current resource utilization level of one or more rendered VNFs. Thereafter, forecasting future resource utilization for the time period based on predictive analysis criteria and the current resource utilization level of the one or more VNFs. The method further comprises a machine learning based inference for determining whether the forecast future resource utilization for said time period is less than a determined optimal resource utilization threshold value of the one or more VNFs. Thereafter, resources of the one or more VNFs to one or more additional workloads are allocated based on the determination of the future resource utilization.
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公开(公告)号:US20220104127A1
公开(公告)日:2022-03-31
申请号:US17484713
申请日:2021-09-24
Applicant: Samsung Electronics Co., Ltd.
Inventor: Karthikeyan SUBRAMANIAM , Karthikeyan NARAYANAN , Naveen KUMAR , Veerabhadrappa Murigeppa GADAG , Vivek SONI
Abstract: The disclosure is related to a method for power management in a wireless communication system. The method includes measuring network resource utilization levels for a plurality of virtual network functions (VNFs) over a time period based on at least one network parameter, determining a behavioral pattern of the network resource utilization levels based on a predictive analysis of the measured network resource utilization levels, forecasting a lean workload time interval of the network resource utilization levels based on the determined behavioral pattern and current network resource utilization levels of the plurality of VNFs, and adjusting central processing unit (CPU) core frequencies of a network server based on the forecasted lean workload time interval.
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