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Towards Adaptive WLAN Frequency Management Using Intelligent Agents 123shows that partial overlapping is worst than a complete overlapping of the frequencychannels. This can be explained from the effectiveness of the collision avoidance(CA) when the two channels are equal. Error rate measurements not reported herealso shows that partial overlapping of frequency channels lead to a larger number oferrors, while total overlapping or non-overlapping channels lead to negligible numbersof errors.The results presented here have been taken into account in 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 overlapping channels lead to lownumbers. However, re-using the same channel on competing access points is betterthat choosing partially overlapping frequency channels. As expected, choosing nonoverlappingchannel leads to the highest score.The optimization function provided in Figure 3 can be adapted if necessary to takeinto account other functions if desired.5 Experiments and Results5.1 Test Bed EnvironmentOur test bed environment is based on four access points (AP) representing 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. Since The AWM agent must communicatebetween WISPs, then it is assumed that WISPs have to be inter-connected. Atleast, WISPs must allow their agents to exchange messages. It is recalled that thesoftware agent platform chosen in 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 points has its own PC acting as a proxy for the accesspoint. The proxy runs the software agent platform and the software agents that havebeen designed to implement the AWM system.Access Points 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 in the AWM agent. Thus associated terminals can be emulated by this featureon each AP.This practical test environment has a limited size and can be used to demonstratethe feasibility of our approach and determine the user experience under different thefrequency adaptation algorithm. Simulation environment has also deployed using theGeneric Network Management Tool (GNMT) [17] described in the next sub-section.In this case, larger network with several tens of access points have been simulated.Comparisons with the practical test environment can also be performed.5.2 Preliminary ResultsIn this section, we briefly present the first results we obtain with our experimentalenvironment. Figure 5 presents the four access points with virtual interference links. Itis recalled that a Virtual Interference Link (VIL) is defined as a communication chan-
124 F. Gamba, J.-F. Wagen, and D. Rossiernel between two access points which are subject to interfere each with other. Currently,VIL topology is determined and configured manually by editing a property filefor each AWM_agent. Automatic VIL discovery mechanism is currently being investigated.Fig. 4. Test environment architectureThe number appearing on each VIL corresponds to the difference of frequencychannel between APs. For example, AP1 is configured on channel 13 and AP2 is alsoon channel 13, therefore the number 0 (=|freq(AP1)-freq(AP2)|=|13-13|) is circled onthe VIL (AP1, AP2).MIB Parameters have been introduced in Section 3.3. In the beginning of our experiment,we have configured each access point on the channel 1. We have then associateda certain number of stations (mobile users) to the access points according to thefollowing scheme: two stations (users) are associated to AP1, three to AP3, five toAP2 and no station is associated to AP4. The numbers depicted on the figure showsthe final (and stable) configuration we obtain after less than 10 minutes. It is importantto see that the optimization algorithm takes into account the possibility to havetwo access points configured with the same channel (AP1 and AP2). As explained inSection 4, having two neighboring access points on the same channels may be consideredas a better solution than having a small difference of frequency.Figure 6 shows the adaptive process over time and, hence, the evolution of the assignedfrequency channel for each access point. A different line profile (size andstyle) is given to each AP.The optimization algorithm must obviously ensure that the process will convergeand avoids cycles. The algorithm we implemented becomes stable after a few minutes.This algorithm is being patented, thus no more details are provided. During theoptimization process, the APs may change several time their frequency channel. Auser associated with a particular access point loose a few packets during the 1 to 3
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Lecture Notes in Computer Science 2
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Samuel Pierre Michel BarbeauEvangel
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PrefaceAd Hoc Networks are wireless
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Program CommitteeG. Alonso, ETHZ, S
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XTable of ContentsResisting Malicio
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50 M. Diha and S. Pierrethe propose
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3BerlinHeidelbergNew YorkHong KongL
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Series EditorsGerhard Goos, Karlsru
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Organizing CommitteeConference Co-c
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Table of ContentsSpace-Time Routing
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Author IndexAlonso, G. 104Bachir, A
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