Free air traffic software for linux

Air Traffic Controller project is an air traffic controller simulation.

Airtraffic is a game/simulator that puts you into an air traffic controllers hotseat. Planes come into your airspace from various directions and you have to guide them safely to their destinations. It uses Python, Corba, and GTK.

TrafficWatch is a system for accounting Internet traffic in a residential college or school type of environment. It consists of a set of scripts and web pages for accounting for internet usage by volume, and is capable of accounting for both Squid proxy traffic and direct IP traffic. It was designed primarily for the use of the colleges of the University of Melbourne, and has been in use in others colleges there since 2001.

TrafficWatch is licensed under the GNU General Public License v2

check_tcptraffic is a simple Nagios plugin to monitor network traffic on Linux systems.

Usage:

usage:
-c crit critical
-w warn warning
-i iface network interface
-r initialize
-v verbose

This is a traffic generator. It is used to check what massive amounts of traffic of certain type will do to an intervening network.

It does not try to measure throughput or response times. It has been made with the question in mind: If 100 clients does simultaneous TCP transfers for 2 days, will my router break? Or can I configure my firewall while 50 people are doing large TCP transfers through the device?

Traffic Prioritizer is designed to run on a Linux router and prioritize users traffic by their bandwidth consumption.

It is aimed to shape the "bandwidth greedy" clients (P2P, YouTube, IPTV, etc.) so that the ones who are just browsing do not lack bandwidth.

Python Traffic Analyzer is a Python base class and sample driver script written to retrieve and manipulate images from the TrafficLand cameras and calculate a numeric value representing the current traffic flow.

PyTrAn, an example driver script, an image collector and an image mask creator are available for download from the link shown at the bottom. To use the PyTrAn package begin by choosing a camera that you wish to analyze, for this example well use the camera captioned above.

We want to construct a mask over the area of the image that we are interested in, namely the road. In this particular example the road takes up the majority of the image but that is not always the case.

We will apply the mask over captured images to fine tune the area over which we are looking for movement. To create the mask we will first need to collect a sequential series of snapshots from the target camera. The image_collector.py script was written for this task:

$ mkdir mask_200003
$ cd mask_200003
$ ../image_collector.py 200003 30
Collecting 30 images...
30

Done.

The script is hard coded to capture images on a 2-second delay. The delay is necessary to ensure the image has changed. I believe 2-seconds to be the absolute minimum. Once complete, 30 images numbered 1 through 30 will be created in the current directory.

We construct a mask from these captured images by creating a diff-image for each sequential image pair and then adding each diff-image together. Naturally, a script was written to automate this task as well:

$ ../mask_maker.py 1 30
Creating a diff for each sequential image pair.
Diffing 29

Creating the initial mask from the first image pair.

Adding the rest of the diffs to the mask.
Masking 29

Done.

A number of .diff files are generated in this process. These files repesent the movement between individual sequence pairs.

The .diff files are simply intermediary files, the important bit is the mask file, which is generated as the sum of all differences.

The mask file may be dirty (as in this case) and require manual cleanup. The basic shape of the road however is clearly visible, evidence that we can with minimal effort automate the mask generation process. Also, this run was conducted at night, day-time images yield better results.

There are a few final steps we need to take before we can use the example PyTrAn driver script. First we need to convert the mask to ASCII (noraw) format:

$ pnmnoraw mask > mask_200003.ascii

Then we need to open an ImageMagick display window and get its X-window-ID using xwininfo. Finally, update camera_id and window_id in pytran_sampling.py and launch the driver:

$ ../pytran_sampling.py
DEBUG> grabbing frame from camera 200003
DEBUG> rotating image: pytran.this > pytran.last
DEBUG> refreshing image in 3 secs
taking a 5 minute sample at various thresholds.
DEBUG> grabbing frame from camera 200003
DEBUG> generating frame diff on pytran.last, pytran.this
DEBUG> displaying image: pytran.diff
DEBUG> converting pytran.diff to ascii
DEBUG> calculating traffic ratio...
ratio[5]: 55%
DEBUG> calculating traffic ratio...
ratio[10]: 52%
...
...
5 minute sample[5]: 67.88
5 minute sample[10]: 42.66
5 minute sample[15]: 30.57
5 minute sample[20]: 23.03
5 minute sample[25]: 18.39
5 minute sample[30]: 14.79
5 minute sample[35]: 12.42
5 minute sample[40]: 10.53
5 minute sample[45]: 9.06
5 minute sample[50]: 7.85

The sampling script will take 5 minute samples at varying color thresholds. The optimal threshold must be manually chosen. Furthermore, you will need to sample the traffic ratios during both heavy and light traffic times to get a good feel for your acceptable range. Also, keep in mind that the traffic ratio value is simply the percent change detected, or in other words the movement detected within the masked region. This means that a completely empty road will register similar values to a road so congested it looks like a parking lot. The time of day can be combined with the traffic ration to determine the logical truth.

With this task implemented and abstracted more complex systems can be built. When I find the time Id like to create a system that will take multiple potential travel routes and times, and during the travel time e-mail the traveler with the best route to take. Another idea I had would be to record the traffic flow values for each camera, for each day and for each half hour interval. Travelers and other interested parties can then analyze traffic patterns to determine the fastest route dependant on date/time.

trafflogger is a conf-based traffic logger. All the logged data can be displayed (graphed) via a web interface. Users can use it to get a global view of network load or to get a closer look at any of the hosts.
This is a conf based traffic logger, each conf log in/out traffic for:
some definable hosts
in a definable device
which match a (optional) definable pcap filter
All the logged data can be displayed (actually graphed) via a web cgi.
So you can get golbal view of your network load and either get a closer look for any of the hosts(very usefull if you are a [mini|wanabe]ISP). Keep in mind that you can make multiples confs for the same host/s, changing only de pcap rule, doing this you are taking photos of your network from multiples angles. You can make a conf to log web traffic, otherone to log mail traffic, and otherone to log kazaa traffic, and finally one to log all traffic. You can also use pcap filter to discrime unwanted traffic for a specific conf.
Main features:
- Coded in Perl
- rrdtool powered
- libpcap powered
- log ip traffic
- traffic grapher/analyzer
- web output
- dynamic ip support

Useful Traffic Accounting Dragon is a traffic accounter that actually gives useful information about traffic instead of stupidly counting incoming/outgoing packets.
Dragon accounts traffic by user, program and timestamp and puts this information into useful correlation.
Dragon is implemented as a Perl script for the backend, using /etc/passwd to automatically get information about user accounts, /proc/net/ to get information about open connections and /proc/ to get information about running processes and which processes currently use which network connection.
All this information can be combined so you can actually see what user caused which traffic using what program and when it happened.
All this information is acquired automatically so the minimal configuration necessary is to tell dragon where it can find its MySQL database.
Enhancements:
Features:
- cleanup on CTRL-C
- add patch for Linux Kernel 2.6.17.7
- for now, graphs are disabled in the webfrontend
- webfrontend has now Total, User and Program tabs
Bugfixes:
- forgot to close a filedescriptor fixed
- use leading zeroes on port numbers in messages about connections that no longer exist
- really fix wait for next minute