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1.发明申请公开(公告)号：US20160378346A1
公开(公告)日：2016-12-29
申请号：US15201467
申请日：2016-07-03
Applicant: Oracle International Corporation
Inventor： Brandon Patrick Byers , Scott Philip Chatley , Thanh Trac Phan , J. Gabriel Gallagher , Peter Jan Pistek
CPC classification number: G06F3/0605 , G06F3/061 , G06F3/0659 , G06F3/067 , G06F16/1827 , H04L67/1097
Abstract: Methods and apparatus for providing a network attached storage system which does not require specialized hardware to operate. In one embodiment, a downloadable software package is provided via a web interface. After a user has downloaded and installed the software package, a sharable volume is created upon a host system. In one embodiment, the sharable volume is adapted to present the contents of one or more remote systems to the host system as a local file, drive, or directory. One or more processes resident in the host system are adapted to intercept a command interpretable by the host system and translate the command into one or more commands interpretable by at least one remote system. The one or more commands are then serviced by at least one remote system and a result set is generated. The result set may then be converted into a format interpretable by the host system and output accordingly.
Abstract translation: 用于提供不需要专门硬件来操作的网络连接存储系统的方法和装置。 在一个实施例中，通过web界面提供可下载的软件包。 用户下载并安装软件包后，在主机系统上创建共享卷。 在一个实施例中，可共享卷适于将一个或多个远程系统的内容作为本地文件，驱动器或目录呈现给主机系统。 驻留在主机系统中的一个或多个进程适于拦截主机系统可解释的命令，并将命令转换成由至少一个远程系统可解释的一个或多个命令。 然后由至少一个远程系统服务一个或多个命令，并且生成结果集。 然后，结果集可以被转换成主机系统可解释的格式并相应地输出。
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Patent Agency Ranking
公开(公告)号：US11362893B2
公开(公告)日：2022-06-14
申请号：US17175209
申请日：2021-02-12
Applicant: Oracle International Corporation
Inventor： Sanjeev R. Sondur , Mark Evan Mills , Brandon Patrick Byers , Prasanta Ranjan Dash , Kenny Clayton Gross
IPC: H04L41/0823 , G06N20/00 , H04L41/084 , H04L41/147 , H04L41/16
Abstract: The embodiments disclosed herein relate to intelligent configuration of a cloud-service gateway based on a pattern recognition algorithm. A machine-learning model is trained to learn the patterns of correlation among many configuration parameters affecting the performance of the system when processing an observed or estimated workload. Training the model may be performed off-line with performance data observed during experiments performed with a variety of configurations and workloads. Once trained, the model may be used to recommend: (a) new configuration parameter values based on constraints of the system being configured, (b) an amount of work that can be performed at a certain performance level when the system is configured with certain parameter values, or (c) the expected performance level when running a certain workload on the system configured with certain configuration parameter values.
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公开(公告)号：US20210021469A1
公开(公告)日：2021-01-21
申请号：US16517236
申请日：2019-07-19
Applicant: Oracle International Corporation
Inventor： Sanjeev R. Sondur , Mark Evan Mills , Brandon Patrick Byers , Prasanta Ranjan Dash , Kenny Clayton Gross
Abstract: The embodiments disclosed herein relate to intelligent configuration of a cloud-service gateway based on a pattern recognition algorithm. A machine-learning model is trained to learn the patterns of correlation among many configuration parameters affecting the performance of the system when processing an observed or estimated workload. Training the model may be performed off-line with performance data observed during experiments performed with a variety of configurations and workloads. Once trained, the model may be used to recommend: (a) new configuration parameter values based on constraints of the system being configured, (b) an amount of work that can be performed at a certain performance level when the system is configured with certain parameter values, or (c) the expected performance level when running a certain workload on the system configured with certain configuration parameter values.
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公开(公告)号：US11079937B2
公开(公告)日：2021-08-03
申请号：US15201467
申请日：2016-07-03
Applicant: Oracle International Corporation , Eric M. Hutchins
Inventor： Brandon Patrick Byers , Scott Philip Chatley , Thanh Trac Phan , J. Gabriel Gallagher , Peter Jan Pistek
IPC: G06F16/00 , G06F3/06 , G06F16/182 , H04L29/08
Abstract: Methods and apparatus for providing a network attached storage system which does not require specialized hardware to operate. In one embodiment, a downloadable software package is provided via a web interface. After a user has downloaded and installed the software package, a sharable volume is created upon a host system. In one embodiment, the sharable volume is adapted to present the contents of one or more remote systems to the host system as a local file, drive, or directory. One or more processes resident in the host system are adapted to intercept a command interpretable by the host system and translate the command into one or more commands interpretable by at least one remote system. The one or more commands are then serviced by at least one remote system and a result set is generated. The result set may then be converted into a format interpretable by the host system and output accordingly.
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公开(公告)号：US20210176127A1
公开(公告)日：2021-06-10
申请号：US17175209
申请日：2021-02-12
Applicant: Oracle International Corporation
Inventor： Sanjeev R. Sondur , Mark Evan Mills , Brandon Patrick Byers , Prasanta Ranjan Dash , Kenny Clayton Gross
Abstract: The embodiments disclosed herein relate to intelligent configuration of a cloud-service gateway based on a pattern recognition algorithm. A machine-learning model is trained to learn the patterns of correlation among many configuration parameters affecting the performance of the system when processing an observed or estimated workload. Training the model may be performed off-line with performance data observed during experiments performed with a variety of configurations and workloads. Once trained, the model may be used to recommend: (a) new configuration parameter values based on constraints of the system being configured, (b) an amount of work that can be performed at a certain performance level when the system is configured with certain parameter values, or (c) the expected performance level when running a certain workload on the system configured with certain configuration parameter values.
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公开(公告)号：US10958521B2
公开(公告)日：2021-03-23
申请号：US16517236
申请日：2019-07-19
Applicant: Oracle International Corporation
Inventor： Sanjeev R. Sondur , Mark Evan Mills , Brandon Patrick Byers , Prasanta Ranjan Dash , Kenny Clayton Gross
Abstract: The embodiments disclosed herein relate to intelligent configuration of a cloud-service gateway based on a pattern recognition algorithm. A machine-learning model is trained to learn the patterns of correlation among many configuration parameters affecting the performance of the system when processing an observed or estimated workload. Training the model may be performed off-line with performance data observed during experiments performed with a variety of configurations and workloads. Once trained, the model may be used to recommend: (a) new configuration parameter values based on constraints of the system being configured, (b) an amount of work that can be performed at a certain performance level when the system is configured with certain parameter values, or (c) the expected performance level when running a certain workload on the system configured with certain configuration parameter values.
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