FW: New Version Notification for draft-fan-deep-performance-visualization-00.txt

"Fan, Peng" <[email protected]> Thu, 20 Feb 2014 00:12:39 +0800
Newsgroups gmane.ietf.ops
Message-ID <[email protected]>
Dear all,

We have posted a document discussing visualizing network performance, and would like to get your attention and feedback. The proposal aims to provide views of network performance for applications/systems/protocols that desire this information to work better. Performance status can be accessed through a unified interface, and comprehensive performance data can be achieved by covering and processing metric values from different areas/perspectives of network.

The document is at http://www.ietf.org/internet-drafts/draft-fan-deep-performance-visualization-00.txt. Any comments are welcome.

Best regards,
Peng

-----Original Message-----
From: [email protected] [mailto:[email protected]] 
Sent: Friday, February 14, 2014 10:49 PM
To: Peng Fan; Peng Fan; Zhen Cao; Zhen Cao
Subject: New Version Notification for draft-fan-deep-performance-visualization-00.txt


A new version of I-D, draft-fan-deep-performance-visualization-00.txt
has been successfully submitted by Peng Fan and posted to the IETF repository.

Name:		draft-fan-deep-performance-visualization
Revision:	00
Title:		Deep Performance Visualization: Use Cases, Requirements and Framework
Document date:	2014-02-14
Group:		Individual Submission
Pages:		7
URL:            http://www.ietf.org/internet-drafts/draft-fan-deep-performance-visualization-00.txt
Status:         https://datatracker.ietf.org/doc/draft-fan-deep-performance-visualization/
Htmlized:       http://tools.ietf.org/html/draft-fan-deep-performance-visualization-00


Abstract:
   Providing deep performance information by the networks is expected in
   many use cases.  This document intends to discuss a unified
   presentation of performance, by investigating use cases that benefit
   from performance information, describing relevant requirements, and
   proposing a framework of how the components work together to enable
   deep performance visualization.

                                                                                  


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