東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back to Search results for [ null ]

Switch To: Labeled | MARC Mode | ISBD

A Restful Web Server with Predictive...

Ready, Michael Tyler.

Linked to FindBook

Google Book

Amazon

博客來

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.
LDR:01833nmm a2200337 4500 001 2208799
005 20191025102416.5
008 201008s2019 ||||||||||||||||| ||eng d
020 $a 9780438903647
035 $a (MiAaPQ)AAI13428244
035 $a (MiAaPQ)southalabama:10643
035 $a AAI13428244
040 $a MiAaPQ $c MiAaPQ
100 1 $a Ready, Michael Tyler. $3 3435851
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.
590 $a School code: 0491.
650 4 $a Computer Engineering. $3 1567821
650 4 $a Electrical engineering. $3 649834
650 4 $a Computer science. $3 523869
690 $a 0464
690 $a 0544
690 $a 0984
710 2 $a University of South Alabama. $b Engineering. $3 3435852
773 0 $t Masters Abstracts International $g 80-09.
790 $a 0491
791 $a M.S.E.E.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13428244