MEASURING AND DETECTING IDLE PROCESSING PERIODS AND IDENTIFYING ROOT CAUSES THEREOF IN CLOUD-BASED, STREAMING APPLICATIONS
A technique for analyzing data in order to detect issues within a cloud-based service is disclosed. Host computing devices in a data center launch virtual machines, where at least some virtual machines run a pipelined stack for a streaming service. Virtual machines in the host computing devices gene...
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creator | Todur, Bipin Larson, Alan Daniel |
description | A technique for analyzing data in order to detect issues within a cloud-based service is disclosed. Host computing devices in a data center launch virtual machines, where at least some virtual machines run a pipelined stack for a streaming service. Virtual machines in the host computing devices generate event data including timestamps. Metadata generated by the pipelined stack during each streaming session is analyzed to identify deadzones in the corresponding host computing device, and the event data is processed to identify potential root causes of the corresponding deadzones. The event data can be generated by the virtual machine hosting the streaming service or by different virtual machines on the same host computing device. A distribution of events of each event type relative to the identified deadzones is determined and an operation of the host computing device can be adjusted based on the distribution. |
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Host computing devices in a data center launch virtual machines, where at least some virtual machines run a pipelined stack for a streaming service. Virtual machines in the host computing devices generate event data including timestamps. Metadata generated by the pipelined stack during each streaming session is analyzed to identify deadzones in the corresponding host computing device, and the event data is processed to identify potential root causes of the corresponding deadzones. The event data can be generated by the virtual machine hosting the streaming service or by different virtual machines on the same host computing device. 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Host computing devices in a data center launch virtual machines, where at least some virtual machines run a pipelined stack for a streaming service. Virtual machines in the host computing devices generate event data including timestamps. Metadata generated by the pipelined stack during each streaming session is analyzed to identify deadzones in the corresponding host computing device, and the event data is processed to identify potential root causes of the corresponding deadzones. The event data can be generated by the virtual machine hosting the streaming service or by different virtual machines on the same host computing device. A distribution of events of each event type relative to the identified deadzones is determined and an operation of the host computing device can be adjusted based on the distribution.</description><subject>AMUSEMENTS</subject><subject>CALCULATING</subject><subject>CARD, BOARD, OR ROULETTE GAMES</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>GAMES</subject><subject>GAMES NOT OTHERWISE PROVIDED FOR</subject><subject>HUMAN NECESSITIES</subject><subject>INDOOR GAMES USING SMALL MOVING PLAYING BODIES</subject><subject>PHYSICS</subject><subject>SPORTS</subject><subject>VIDEO GAMES</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNjTEKwkAQRdNYiHqHAVsDJkHQct2dmIFkN-zMFlYhyFqJBmLl6SXBA1h93ufBWyafBhUHT_YCyhowKKhlIjI1QuudRuaJW_TkDM8WGbRC5XX6vXMCWgVGBqnQoyuBLOjaBZOeFaPZAYtH1cyNtq1JKyFneZ0s7v1jjJvfrpJtiaKrNA6vLo5Df4vP-O4C5_s8z07F4XBUWfGf9QXxIzt-</recordid><startdate>20220623</startdate><enddate>20220623</enddate><creator>Todur, Bipin</creator><creator>Larson, Alan Daniel</creator><scope>EVB</scope></search><sort><creationdate>20220623</creationdate><title>MEASURING AND DETECTING IDLE PROCESSING PERIODS AND IDENTIFYING ROOT CAUSES THEREOF IN CLOUD-BASED, STREAMING APPLICATIONS</title><author>Todur, Bipin ; Larson, Alan Daniel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2022193558A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2022</creationdate><topic>AMUSEMENTS</topic><topic>CALCULATING</topic><topic>CARD, BOARD, OR ROULETTE GAMES</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>GAMES</topic><topic>GAMES NOT OTHERWISE PROVIDED FOR</topic><topic>HUMAN NECESSITIES</topic><topic>INDOOR GAMES USING SMALL MOVING PLAYING BODIES</topic><topic>PHYSICS</topic><topic>SPORTS</topic><topic>VIDEO GAMES</topic><toplevel>online_resources</toplevel><creatorcontrib>Todur, Bipin</creatorcontrib><creatorcontrib>Larson, Alan Daniel</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Todur, Bipin</au><au>Larson, Alan Daniel</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>MEASURING AND DETECTING IDLE PROCESSING PERIODS AND IDENTIFYING ROOT CAUSES THEREOF IN CLOUD-BASED, STREAMING APPLICATIONS</title><date>2022-06-23</date><risdate>2022</risdate><abstract>A technique for analyzing data in order to detect issues within a cloud-based service is disclosed. Host computing devices in a data center launch virtual machines, where at least some virtual machines run a pipelined stack for a streaming service. Virtual machines in the host computing devices generate event data including timestamps. Metadata generated by the pipelined stack during each streaming session is analyzed to identify deadzones in the corresponding host computing device, and the event data is processed to identify potential root causes of the corresponding deadzones. The event data can be generated by the virtual machine hosting the streaming service or by different virtual machines on the same host computing device. A distribution of events of each event type relative to the identified deadzones is determined and an operation of the host computing device can be adjusted based on the distribution.</abstract><oa>free_for_read</oa></addata></record> |
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subjects | AMUSEMENTS CALCULATING CARD, BOARD, OR ROULETTE GAMES COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING GAMES GAMES NOT OTHERWISE PROVIDED FOR HUMAN NECESSITIES INDOOR GAMES USING SMALL MOVING PLAYING BODIES PHYSICS SPORTS VIDEO GAMES |
title | MEASURING AND DETECTING IDLE PROCESSING PERIODS AND IDENTIFYING ROOT CAUSES THEREOF IN CLOUD-BASED, STREAMING APPLICATIONS |
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