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公开(公告)号：US10608901B2
公开(公告)日：2020-03-31
申请号：US15647549
申请日：2017-07-12
Applicant: Cisco Technology, Inc.
Inventor： Chirag Tayal , Esha Desai , Paddu Krishnan
Abstract: Disclosed is a method that includes collecting first temporal statistics for a port element in a computing environment, collecting second temporal statistics for a switch element in the computing environment, collecting third temporal statistics for the computing environment generally, computing a spatial correlation between network features and network elements comprising the port element and the switch element and computing, via a machine learning technique, a port dynamic weight for the port element and a switch dynamic weight for the switch element. The method can also include scheduling workload to consume compute resources within the compute environment based at least in part on the port dynamic weight for the port element and the switch dynamic weight for the switch element.
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2.发明申请公开(公告)号：US20200236012A1
公开(公告)日：2020-07-23
申请号：US16833343
申请日：2020-03-27
Applicant: Cisco Technology, Inc.
Inventor： Chirag Tayal , Esha Desai , Paddu Krishnan
Abstract: Disclosed is a method that includes collecting first temporal statistics for a port element in a computing environment, collecting second temporal statistics for a switch element in the computing environment, collecting third temporal statistics for the computing environment generally, computing a spatial correlation between network features and network elements comprising the port element and the switch element and computing, via a machine learning technique, a port dynamic weight for the port element and a switch dynamic weight for the switch element. The method can also include scheduling workload to consume compute resources within the compute environment based at least in part on the port dynamic weight for the port element and the switch dynamic weight for the switch element.
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公开(公告)号：US11233710B2
公开(公告)日：2022-01-25
申请号：US16833343
申请日：2020-03-27
Applicant: Cisco Technology, Inc.
Inventor： Chirag Tayal , Esha Desai , Paddu Krishnan
Abstract: Disclosed is a method that includes collecting first temporal statistics for a port element in a computing environment, collecting second temporal statistics for a switch element in the computing environment, collecting third temporal statistics for the computing environment generally, computing a spatial correlation between network features and network elements comprising the port element and the switch element and computing, via a machine learning technique, a port dynamic weight for the port element and a switch dynamic weight for the switch element. The method can also include scheduling workload to consume compute resources within the compute environment based at least in part on the port dynamic weight for the port element and the switch dynamic weight for the switch element.
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4.发明申请公开(公告)号：US20190020555A1
公开(公告)日：2019-01-17
申请号：US15647549
申请日：2017-07-12
Applicant: Cisco Technology, Inc.
Inventor： Chirag Tayal , Esha Desai , Paddu Krishnan
Abstract: Disclosed is a method that includes collecting first temporal statistics for a port element in a computing environment, collecting second temporal statistics for a switch element in the computing environment, collecting third temporal statistics for the computing environment generally, computing a spatial correlation between network features and network elements comprising the port element and the switch element and computing, via a machine learning technique, a port dynamic weight for the port element and a switch dynamic weight for the switch element. The method can also include scheduling workload to consume compute resources within the compute environment based at least in part on the port dynamic weight for the port element and the switch dynamic weight for the switch element.
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