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PingER Management 1
Error Reporting Model for Ping End-to-End Reporting
(PingER Management)
PingER Management 2
Project Scope
Administrators of PingER face many problems in handling the system. Finding out the sites/nodes that are down and Finding anomalies in the data ,collected at the
Archive site They have to do many of these tasks manually
and on a daily basis. This project solves these problems It is designed to be a time saver for the
Administrators of PingER.
PingER Management 3
Project Scope
This system automatically Emails the current status of the sites and nodes to the
Administrator Publishes the latest results regarding down sites and down
nodes on the web Finds out Anomalous sites based on different statistical
techniques Finds out invalid data and mismatch TLD’s (Top Level
Domains) in the PingER database Makes various histograms and pie charts to help the
Administrator to find the current status of the PingER system
PingER Management 4
PingER ManagementArchitecture
PingER Management 5
System Architecture
Web Server
Apache Web Server
PERL
Interpreter
ModuleDatabase
PERL DBIHTTP
PingER Management 6
PingER Management 7
Down Sites and NodesFilter
Anomaly Detection Engine Automatic report
generation tool Dramatic-Events Anomaly
Detection Engine Data Discrepancy finder
and solver
3.PROCESSING
1.DOWNLOADS FILE
2.SAVE FILE
4.1 MAIN USERPAGE
PingER Management
Down Sites and Nodes Filter
Anomaly Detection Engine
Automatic report generation tool
Dramatic-Events Anomaly Detection Engine
Data Discrepancy finder and solver
4.2 GENERATE PAGE
4.3 LINKS
TSV
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Major components of the system
1. Down Sites and Nodes Filter
2. Anomaly Detection Engine
3. Automatic report generation tool
4. Dramatic-Events Anomaly Detection Engine
5. Data Discrepancy finder and solver
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1. Filters for finding down Sites and Nodes
Create filters, which indicate Monitoring sites and Monitored nodes, that are not available.
That is , which Monitored Nodes and Monitoring Sites have not responded in the last week (specified time)
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2. Anomaly Detection Engine
To check anomalous behaviors in the data like RTT (Round Trip Time), Packet loss and derived throughput and report that to the Administrators. Look at the minimum RTT for a host that is supposedly
in some country or regions Compares this RTT with other hosts in the same
region If it was way below, the RTT of other hosts in the
region than flag it.
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3. Automatic report generation tool
An Automatic report generation tool for the management that generates daily, monthly, yearly reports regarding problems in monitoring data.
graph showing which sites were down at what time Reports showing Anomalies in RTT.
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4. Dramatic-Events Anomaly Detection Engine
To check anomalous dramatic events in RTT, Packet loss and derived throughput and report these events to the Administrators.
The min RTT dropped by a factor of two There was no response for a long period of time
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5. Data Discrepancy finder
Find discrepancies in the input data
At the time of registration of the monitored hosts, the data entered might be incorrect and incomplete;
As a result the monitored host remains “not-Set”
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Current Status
The project has been installed at NIIT and is up and running.
Some of the problems resolved :
Automation of data collection Generation of graphs and tables in case of non-
availability of new data.
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Future Goals
Evaluation and Redesign of MySQL database to reduce redundancy among tables.
Installation of the improved version at SLAC.