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Created by Zafar Gilani, sent by email 6/14/2010. It compares trilateration (3 landmarks) with mulitlateration (3 to 5 landmarks) giving the target hostname, IP address, its actual lat/longs, the targets estimated location, landmark hostnames, landmark lat/longs and error between estimated and actual | |
Created by Fida, sent by email 6/10/2010. It is a compendium comparing the several of the geolocation methods including:CBG, SOI, TBG, TBG_Updtaed, Apollonius, Triilateration | |
File Sent by Zafar 3.08pm Jun 1 2010. Compares improved trilateration (by Farrah) vs CBG trilateration. | |
From Zafar by email 6/2/2010 2:06am. So far what I've gathered from doing this: There are so-called "bad" landmark estimate values in target files which causes these. There is also a portion in the code that deliberately ignores such values (see 1 under "Results, observations and explanation" here). By restricting n to 10 and 4 I've managed to remove those "bad" values for 39 and 14 targets respectively. | |
From Zafar, direct upload on 6/19/2010 1:41am. This spreadsheet provides a histogram of the errors for 74 overlapping results between CBG trilateration and improved trilateration (by Farrah). | |
From Zafar, direct upload on 7/14/2010 6:46pm. This file contains all sorts of detailed information regarding all studied geolocation techniques. Furthermore the spreadsheet also contains graphs for: |
Procedure to generate analysis for all studied geolocation techniques
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- The first step requires us to create multiple CSV files. Each CSV file will correspond to an independent geolocation technique. Open a spreadsheet already created and copy target IPs and error distance columns into a new spreadsheet and save it as a CSV (.csv) file. Name it against the geolocation technique such as apollonius.csv for Apollonius. Table 2 below shows geolocation technique against its file name.
- It is a possible that for some geolocation techniques, we might not have IP addresses, instead we might have hostnames. To handle such a case we have created a shell script GetIPFromHostName.sh to convert a list of hostnames into IP addresses. To do this, copy the hostnames to HOSTS variable inside GetIPFromHostName.sh. These must be separated by white-space or new line character. Run the script to get the print out of IP address list at the terminal.
- Put these under a csv directory. Put the csv directory and Node_info.txt file alongside CreateCSVForComparison.pl script. Table 3 below provides links to these files.
- Execute CreateCSVForComparison.pl script. This will generate all-analysis.csv file containing data in the following format. This will contain all data including null value for those targets for which a geolocation technique didn't find any estimate results. The name of each technique represents column of error distance values.
- Open this all-analysis.csv file and convert this to a spreadsheet for analysis.
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Table 3 below provides links to the files above in csv directory, Node_info.txt file, all-analysis.csv file and CreateCSVForComparison.pl script.mentioned above.
File | Description | ||
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Script that takes hostnames and converts those to IP addresses. The hostnames list must be copied to HOSTS variable inside the script, each value separated by white-space or new line character. This script outputs a list of IP addresses in the same order as that of hostnames. | File | Description||
Contains all the csv files. | |||
Contains information such as hostname, IP addresses, Regions, Lat/Longs, etc. for 182 targets. | |||
An amalgamation of all the geolocation techniques and their error distances against the IP addresses and other information. The format is shown above in the box titled "data format of all-analysis.csv". | |||
Script that takes csv files from csv directory and Node_info.txt file as inputs and processes out all-analysis.csv file as output. |
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Known issues
Output file formatting issues:
Once all-analysis.csv is generated, don't directly copy it to Windows since there are some formatting issues in such a case. It won't open correctly in Microsoft Excel. So in order to make this right. Open all-analysis.csv via vim (on Linux) and copy paste the text into Windows notepad (later save it as all-analysis.csv). Once done press CTRL+H to find and replace ^M characters that are read by Linux vim but not my by Microsoft Excel and probably therefore causes all sorts of formatting issues.
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