Free traffic shaping software for linux

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.

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

IP Traffic Meter is a traffic counter for IPv4 addresses. It uses the DB4 database from Berkeley to keep its counters, the pcap library for monitoring, and the gd library from Boutel to create graphics. The results are displayed in JPEG graphics on an HTML webpage.
Enhancements:
- With ipmeter you can monitor the traffic made by some IPs. It produces daily, weekly, monthly and yearly statistics into jpg graphics. It uses db4 database from Berkeley to keep its internal counters, and gd library from Boutell to create jpg graphic.

IPChains is a Perl module to create and manipulate ipchains via Perl.

SYNOPSIS

use IPChains;
$fw = IPChains->new(-option => value, ... ); $fw->append(chain);

This module acts as an interface to the ipchains(8) userspace utility by Paul "Rusty" Russell (http://www.rustcorp.com/linux/ipchains/). It attempts to include all the functionality of the original code with a simplified user interface via Perl. In addition, plans for log parsing facilities, an integrated interface to ipmasqadm, and possibly traffic shaping are slated for up and coming versions.
The new() and attribute() methods support the following options:

Source

Specifies origination address of packet. Appending hostmask to this address using a / is OK, as well as specifying it separately (see SourceMask).

SourceMask

Hostmask for origination address. Can either be in 24 or 255.255.255.0 style.

SourcePort

Specific port or port range (use xxx:xxx to denote range), requires specific protocol specification.

Dest

Specifies destination address of packet. Appending hostmask to this address using a / is OK, as well as specifying it separately (see DestMask)

DestMask

Destination address, (see SourceMask).

DestPort

Destination Port, (see SourcePort).

Prot

Protocol. Can be tcp, udp, icmp, or all. Required for specifying specific port(s).

ICMP

ICMP Name/Code (in place of port when ICMP is specified as protocol).

Here is a small table of some of the most common ICMP packets:

Number Name Required by

0 echo-reply ping
3 destination-unreachable Any TCP/UDP traffic.
5 redirect routing if not running
routing daemon
8 echo-request ping
11 time-exceeded traceroute

Rule

Target. Can be ACCEPT, DENY, REJECT, MASQ, REDIRECT, RETURN, or a user-defined chain. Note: This is case sensitive.

Interface

Specify a specify interface as part of the criteria (ie, eth0, ppp0, etc.).

Fragment

Rule only refers to second and further fragments of fragmented packets (1 or 0).

Bidir

Makes criteria effective in both directions (1 or 0).

Verbose

Set verbose option for setting rules or list() (1 or 0).

Numeric

Show output from list() in numeric format. No DNS lookups, etc.. (1 or 0).

Log

Enable kernel logging (via syslog, kern.info) of matched packets (1 or 0).

Output

Copy matching packets to the userspace device (advanced).

Mark

Mark matching packets with specified number (advanced).

TOS

Used for modifying the TOS field in the IP header. Takes 2 args, AND and XOR masks, (ie, (TOS => ["0x01", "0x10"])). This feature is highly untested.
The first mask is ANDed with the packets current TOS, and the second mask is XORed with it. Use the following table for reference:

TOS Name Value Typical Uses

Minimum Delay 0x01 0x10 ftp, telnet
Maximum Throughput 0x01 0x08 ftp-data
Maximum Reliability 0x01 0x04 snmp
Minimum Cost 0x01 0x02 nntp

Exact

Display exact numbers in byte counters instead of numbers rounded in Ks, Ms, or Gs (1 or 0).

SYN

Only match TCP packets with the SYN bit set and the ACK and FIN bits cleared (1 or 0).

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.

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.

PostArabic project is used to provide Arabic shaping for the map display in DCMMS.
The PostArabic package provides Arabic shaping functionality for PostgreSQL. PostArabic is available from http://dcmms.sourceforge.net.
The package adds the following functions to PostgreSQL:
text shape_arabic(text)
text unshape_arabic(text)
text str_reverse(text)
Enhancements:
- This release adds the bidi_reorder() function that provides better results than str_reorder() for numbers embedded in Arabic text.
- In addition, it fixes a build problem on Linux where libarabic.dll was referenced in arabic.sql instead of arabic.so.