Understanding and enlivening AQM workings using computer simualtion

Understanding and enlivening AQM workings using computer simualtion

[Abstract]: Undeniably, computer simulation is an effective tool to help understand and analyze complex processes and systems in various areas. In recent years, many educators adopt computer simulation technology in the teaching of some topics or courses which include dynamic interactions between components. For years, many concepts of networking have been taught based on textual or other static visual materials. And many researcher have shown that illustrating dynamic scenario using static and lecture-based paradigms compromises the teaching effectiveness. This problem on computer network education prompted us to use graphical simulation. Courses related to computer communication and networking can be benefitted if
computer simulation is wisely adopted.

In this paper, we describe a study in which we count on computer simulation to illustrate important and complicated algorithms of congestion control and queue management in the TCP/IP protocol suites. Comparing with current queue management techniques, Active Queue Management(AQM) is an innovative mechanism in router packet scheduling. We noticed that AQM is a promising technique and might be implemented in new generation routers. However, the concepts and internal workings of AQM schema are difficult for researchers and students to understand. Thus, we designed an interactive software to dynamically visualize the AQMs’principles and internal workings. The implementation of simulation package used Java technology due to that Java is an object-oriented programming language with extensive build-in graphical facilities and multi-threading mechanism.

In our software package, we have implemented the traditional Drop Tail(DT) and two representative AQM schemas: Random Early Detection(RED) and BLUE. It allows users to conduct their own experiments by entering different parameters for each of the algorithms, as shown in the figure below. The structure of simulation package follows the Model-View-Controller paradigm which separates the development of network models from visualization and control of the models. The animation visually describes the internal working process of the algorithms with a plot diagram, which displays the variations of the router queue size. We also compared the simulation results of the three queue management algorithms. From the animating simulation, we can easily see the difference of performance between AQM and DT. The main strength of our AQM simulator is ease of use when compared with other professional simulation tools such as NS2 or OMNet++, because users do not need solid programming capability to build the simulation from scratch. By using graphical animation, learners can directly access the internal process of the three queue management algorithms. We have received very positive feedbacks from network professionals and University lecturers for using this simulation software.

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