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We have already discussed measurement techniques. But while real measurements have an unquestionable authenticity, a number of problems are associated with real measurements. Lack of
reproducibility is one problem. Scale problems, such as the cost of increasing the size of the test network, are another concern. If you are considering implementation issues, then direct measurement
can only be done late in the development cycle, compounding the cost of mistakes. Emulation and simulation offer lower-cost alternatives.
Simulators have the advantages of being relatively cheap, providing highly reproducible results, scaling very well and inexpensively, and giving results quickly. It is generally very straightforward to
customize the degree of detail in reports so you can focus on just what is of interest. Simulations vary in degree of abstraction. The greater the degree of abstraction, the easier it is to focus on what is of
interest at the cost of lost realism. However, if a simulation is poorly designed, the results can have little basis in reality. Also, some simulators may be implemented primarily for one type of use and
may not be appropriate for other uses. From a troubleshooting perspective, you might use a simulator to further investigate a hypothesis. Simulators would provide a way to closely examine behavior to
confirm or refute the hypothesis without creating problems on a production network.
Emulators lie between simulators and live systems. They allow controlled experiments with a high degree of reproducibility. They make it much easier to create the type of traffic or events of interest.
They also provide a mechanism to test real systems effectively. For example, an emulator might duplicate or approximate the behavior of an attached device or network. A router emulator might drop
traffic or inject traffic into the actual test network. On the downside, some emulators tend to be very specialized and are usually platform specific. For troubleshooting, an emulator could be used to stress
a network.
9.2.1 NISTNet
NIST Network Emulation Tool NISTNet is a general purpose tool that can be used to emulate the dynamics in an IP network. It was developed by the National Institute of Standards and Technology
NIST and is implemented as an extension to the Linux operating system through a kernel module. Unlike many emulators, NISTNet supports a fairly heterogeneous approach to emulation. And since it
will run on a fairly standard platform, it is remarkably inexpensive to set up and use.
NISTNet allows you to use a Linux system configured as a router, through an X Window interface, to model or emulate a number of different scenarios. For example, you can program both fixed and
variable packet delays and random reordering of packets. Packets can be dropped either randomly uniform distribution or based on congestion.
[2]
Random duplication of packets, bandwidth limitations, or asymmetric bandwidth can all be programmed into NISTNet. You can also program in jitter and do
basic quality-of-service measurements. NISTNet can be driven by traces from measurements from existing networks. User-defined packet handlers can be added to the system to add timestamps, do
data collection, generate responses for emulated clients, and so forth.
[2]
Gateway emulators that support this kind of behavior are sometimes less charitably called flakeways.
9.2.2 ns and nam
If you want to consider simulations, you should first look into a pair of programs, ns and nam. ns is a network simulator, while nam is a network visualization tool. Both are under development by the
Virtual InterNetwork Testbed VINT project, a DARPA-funded research project whose goal is to produce a simulator for studying scale and protocol interactions. VINT is a collaborative project that
involves USC, Xerox PARC, LBNL, and UCB.
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ns is derived from earlier simulation projects such as REAL and has gone through a couple of incarnations. The kernel is written in C++, while user scripts are written in MITs Object Tool
Command Language OTCL, an object-oriented version of Tcl. With any simulation software, you should expect a steep learning curve, and ns is no exception. Youll need to learn how to use the
product, and you will also need a broad knowledge of simulations in general. To use ns, youll need to learn how to write scripts in OTCL.
Fortunately, the ns project provides a wealth of documentation. The Unix manpage is more than 30 pages and displays the typical unreadable terseness associated with Unix manual pages—great for
looking up something you already know arguably the intended use but abysmal for learning something new. There is also a downloadable manual that runs more than 300 pages. However, the
best place to start is with Marc Greiss tutorial. It is a more manageable 50 pages and introduces the scripting language in a series of readable examples.
One problem with simulations is that they can produce an overwhelming amount of information. Even worse, simulation results describe dynamic events that are difficult to interpret when viewed statically.
nam is a visualization tool that animates network simulations. It is hard to convey the real flavor of nam from a single black-and-white snapshot, but
Figure 9-1 should give you some idea of its value.
Figure 9-1. nam example
This is output from one of the sample scripts that comes with the program. The basic topology of the network should be obvious. Packets are drawn as colored rectangles. Different colors are used for
different sources. As the animation is played, you see the packets generated, queued at devices, move across the network, and occasionally, dropped from the network. Node 6 in the figure shows a stack of
packets that have been queued and one packet below the node that has been dropped. Dropped packets fall to the bottom of the screen. The control buttons at the top are used just as you would
expect—to play, stop, or rewind the animation.
NISTNet, ns, and nam are all described as ongoing projects. But all three are more polished than many completed projects.
9.3 Microsoft Windows
