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Page 2 Lecture Notes in Computer Science 2865 Edited by G. Goos ...

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Towards Adaptive WLAN Frequency Management Us<strong>in</strong>g Intelligent Agents 123shows that partial overlapp<strong>in</strong>g is worst than a complete overlapp<strong>in</strong>g of the frequencychannels. This can be expla<strong>in</strong>ed from the effectiveness of the collision avoidance(CA) when the two channels are equal. Error rate measurements not reported herealso shows that partial overlapp<strong>in</strong>g of frequency channels lead to a larger number oferrors, while total overlapp<strong>in</strong>g or non-overlapp<strong>in</strong>g channels lead to negligible numbersof errors.The results presented here have been taken <strong>in</strong>to account <strong>in</strong> the design of our optimizationfunction represented on Figure 3: a value between 0 and 100 is assigned tothe difference between 2 channels.The optimization function is not monotone. Partially overlapp<strong>in</strong>g channels lead to lownumbers. However, re-us<strong>in</strong>g the same channel on compet<strong>in</strong>g access po<strong>in</strong>ts is betterthat choos<strong>in</strong>g partially overlapp<strong>in</strong>g frequency channels. As expected, choos<strong>in</strong>g nonoverlapp<strong>in</strong>gchannel leads to the highest score.The optimization function provided <strong>in</strong> Figure 3 can be adapted if necessary to take<strong>in</strong>to account other functions if desired.5 Experiments and Results5.1 Test Bed EnvironmentOur test bed environment is based on four access po<strong>in</strong>ts (AP) represent<strong>in</strong>g two WirelessInternet Service Providers (WISPs). An Autonomous WLAN Management(AWM) agent is connected to each AP and each AP is configured with a Service SetIdentifier (SSID) that characterizes the WISP. S<strong>in</strong>ce The AWM agent must communicatebetween WISPs, then it is assumed that WISPs have to be <strong>in</strong>ter-connected. Atleast, WISPs must allow their agents to exchange messages. It is recalled that thesoftware agent platform chosen <strong>in</strong> this work simplify greatly this exchange of messages.Figure 4 shows the test environment, its architecture and the exchange of messages.Each of the 4 access po<strong>in</strong>ts has its own PC act<strong>in</strong>g as a proxy for the accesspo<strong>in</strong>t. The proxy runs the software agent platform and the software agents that havebeen designed to implement the AWM system.Access Po<strong>in</strong>ts are Cisco Aironet 350 products. The AWM Agent platform is basedon Jade platform and runs on Pentium-III PCs. Wireless LAN clients are laptops withPCMCIA WLAN cards. To test traffic congestion, we have implemented a clientemulator <strong>in</strong> the AWM agent. Thus associated term<strong>in</strong>als can be emulated <strong>by</strong> this featureon each AP.This practical test environment has a limited size and can be used to demonstratethe feasibility of our approach and determ<strong>in</strong>e the user experience under different thefrequency adaptation algorithm. Simulation environment has also deployed us<strong>in</strong>g theGeneric Network Management Tool (GNMT) [17] described <strong>in</strong> the next sub-section.In this case, larger network with several tens of access po<strong>in</strong>ts have been simulated.Comparisons with the practical test environment can also be performed.5.2 Prelim<strong>in</strong>ary ResultsIn this section, we briefly present the first results we obta<strong>in</strong> with our experimentalenvironment. Figure 5 presents the four access po<strong>in</strong>ts with virtual <strong>in</strong>terference l<strong>in</strong>ks. Itis recalled that a Virtual Interference L<strong>in</strong>k (VIL) is def<strong>in</strong>ed as a communication chan-

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