公开(公告)号：US10558543B2

公开(公告)日：2020-02-11

申请号：US15806187

申请日：2017-11-07

Applicant: VMware, Inc.

Inventor： Ashot Nshan Harutyunyan ,  Arnak Poghosyan ,  Naira Movses Grigoryan ,  Vahe Khachikyan ,  Nshan Sharoyan

IPC: G06F15/173 ,  G06F11/30

Abstract: The current document is directed to methods and systems that collect metric data within computing facilities, including large data centers and cloud-computing facilities. In a described implementation, two or more metric-data sets are combined to generate a multidimensional metric-data set. The multidimensional metric-data set is compressed for efficient storage by clustering the multidimensional data points within the multidimensional metric-data set to produce a covering subset of multidimensional data points and by then representing the multidimensional-data-point members of each cluster by a cluster identifier rather than by a set of floating-point values, integer values, or other types of data representations. The covering set is constructed to ensure that the compression does not result in greater than a specified level of distortion of the original data.

公开(公告)号：US20190138420A1

公开(公告)日：2019-05-09

申请号：US15806187

申请日：2017-11-07

Applicant: VMware, Inc.

Inventor： Ashot Nshan Harutyunyan ,  Arnak Poghosyan ,  Naira Movses Grigoryan ,  Vahe Khachikyan ,  Nshan Sharoyan

IPC: G06F11/30

Abstract: The current document is directed to methods and systems that collect metric data within computing facilities, including large data centers and cloud-computing facilities. In a described implementation, two or more metric-data sets are combined to generate a multidimensional metric-data set. The multidimensional metric-data set is compressed for efficient storage by clustering the multidimensional data points within the multidimensional metric-data set to produce a covering subset of multidimensional data points and by then representing the multidimensional-data-point members of each cluster by a cluster identifier rather than by a set of floating-point values, integer values, or other types of data representations. The covering set is constructed to ensure that the compression does not result in greater than a specified level of distortion of the original data.

公开(公告)号：US10901869B2

公开(公告)日：2021-01-26

申请号：US15805424

申请日：2017-11-07

Applicant: VMware, Inc.

Inventor： Arnak Poghosyan ,  Ashot Nshan Harutyunyan ,  Naira Movses Grigoryan ,  Vaghinak Saghatelyan ,  Vahe Khachikyan

IPC: G06F11/30 ,  G06F11/34

Abstract: The current document is directed to methods and systems that collect metric data within computing facilities, including large data centers and cloud-computing facilities. In a described implementation, lower and higher metric-data-value thresholds are used to partition collected metric data into outlying metric data and inlying metric data. The inlying metric data is quantized to compress the inlying metric data and adjacent data points having the same quantized metric-data values are eliminated, to further compress the inlying metric data. The resulting compressed data includes original metric-data representations for outlier data points and compressed metric-data representations for inlier data points, providing accurate restored metric-data values for significant data points when compressed metric data is decompressed.

公开(公告)号：US20190138419A1

公开(公告)日：2019-05-09

申请号：US15805424

申请日：2017-11-07

Applicant: VMware, Inc.

Inventor： Arnak Poghosyan ,  Ashot Nshan Harutyunyan ,  Naira Movses Grigoryan ,  Vaghinak Saghatelyan ,  Vahe Khachikyan

IPC: G06F11/30

Abstract: The current document is directed to methods and systems that collect metric data within computing facilities, including large data centers and cloud-computing facilities. In a described implementation, lower and higher metric-data-value thresholds are used to partition collected metric data into outlying metric data and inlying metric data. The inlying metric data is quantized to compress the inlying metric data and adjacent data points having the same quantized metric-data values are eliminated, to further compress the inlying metric data. The resulting compressed data includes original metric-data representations for outlier data points and compressed metric-data representations for inlier data points, providing accurate restored metric-data values for significant data points when compressed metric data is decompressed.

公开(公告)号：US20210124665A1

公开(公告)日：2021-04-29

申请号：US17140065

申请日：2021-01-02

Applicant: VMware, Inc.

Inventor： Arnak Poghosyan ,  Ashot Nshan Harutyunyan ,  Naira Movses Grigoryan ,  Vaghinak Saghatelyan ,  Vahe Khachikyan

IPC: G06F11/30 ,  G06F11/34

Abstract: The current document is directed to methods and systems that collect metric data within computing facilities, including large data centers and cloud-computing facilities. In a described implementation, lower and higher metric-data-value thresholds are used to partition collected metric data into outlying metric data and inlying metric data. The inlying metric data is quantized to compress the inlying metric data and adjacent data points having the same quantized metric-data values are eliminated, to further compress the inlying metric data. The resulting compressed data includes original metric-data representations for outlier data points and compressed metric-data representations for inlier data points, providing accurate restored metric-data values for significant data points when compressed metric data is decompressed.

公开(公告)号：US09742435B1

公开(公告)日：2017-08-22

申请号：US15188834

申请日：2016-06-21

Applicant: VMware, Inc.

Inventor： Arnak Poghosyan ,  Ashot Nshan Harutyunyan ,  Naira Movses Grigoryan ,  Vahe Khachikyan ,  Meruzhan Kerobyan

IPC: H03M7/34 ,  H03M7/30 ,  H03M7/40 ,  H03M7/46 ,  H04L29/08

CPC classification number: H03M7/3082 ,  G06F11/34 ,  H03M7/30 ,  H03M7/3064 ,  H03M7/40 ,  H03M7/46 ,  H04L29/08072 ,  H04L29/08144 ,  H04L41/046 ,  H04L43/04 ,  H04L43/0817 ,  H04L69/04

Abstract: The current document is directed to a multi-stage metric-data compression method and subsystem for compressing metric data collected and stored within distributed computing systems to facilitate computer-system management and administration. In a described implementation, metric data is partitioned into constant metric data, low-variability metric data, and high-variability metric data. High-variability metric data is compressed by identifying a set of basis metrics, or independent metrics, with respect to which a remaining set of dependent metrics can be expressed using coefficient multipliers. The high-variability metric data can then be stored as a set of independent metrics and set of coefficients, along with a small amount of additional data.