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A Restful Web Server with Predictive...

Ready, Michael Tyler.

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A Restful Web Server with Predictive Failure and Performance Monitoring.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Restful Web Server with Predictive Failure and Performance Monitoring./
Author:	Ready, Michael Tyler.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	96 p.
Notes:	Source: Masters Abstracts International, Volume: 80-09.
Contained By:	Masters Abstracts International80-09.
Subject:	Computer Engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13428244
ISBN:	9780438903647

A Restful Web Server with Predictive Failure and Performance Monitoring.
Ready, Michael Tyler.

A Restful Web Server with Predictive Failure and Performance Monitoring. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 96 p.

Source: Masters Abstracts International, Volume: 80-09.

Thesis (M.S.E.E.)--University of South Alabama, 2019.

This item must not be sold to any third party vendors.

Statistical analysis is a critical part of assessing computing systems. Data-based estimates of performance and failure rates can help organizations make cost efficient decisions. Modern monitoring software relies heavily on HTTP interfacing. Specifically, RESTful API's have become an industry standard for reporting system state over Internet connections. However, the Simple Networking Management Protocol (SNMP) is currently the only source of much performance and system data. Therefore, a RESTful API web service monitoring a computer could reduce effort and overhead in acquiring statistical data. Our service consists of the following components: 1. Machine Learning-based Predicitve 2. Real-time Statistics Monitoring. 3. Authentication.

ISBN: 9780438903647Subjects--Topical Terms:

1567821
Computer Engineering.

A Restful Web Server with Predictive Failure and Performance Monitoring.
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245 1 0 $a A Restful Web Server with Predictive Failure and Performance Monitoring.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 96 p.
500 $a Source: Masters Abstracts International, Volume: 80-09.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Lazarou, Georgios.
502 $a Thesis (M.S.E.E.)--University of South Alabama, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a Statistical analysis is a critical part of assessing computing systems. Data-based estimates of performance and failure rates can help organizations make cost efficient decisions. Modern monitoring software relies heavily on HTTP interfacing. Specifically, RESTful API's have become an industry standard for reporting system state over Internet connections. However, the Simple Networking Management Protocol (SNMP) is currently the only source of much performance and system data. Therefore, a RESTful API web service monitoring a computer could reduce effort and overhead in acquiring statistical data. Our service consists of the following components: 1. Machine Learning-based Predicitve 2. Real-time Statistics Monitoring. 3. Authentication.
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650 4 $a Computer Engineering. $3 1567821
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13428244