Wireless Ad Hoc and Sensor Networks

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Congestion Control in ATM Networks and the Internet 1010.0450.040.035Feedback delay = 0ThresholdAdaptiveOne layerTwo layer w/o trainingTwo layer with training0.03Cell loss ratio0.0250.020.0150.010.0050150 200 250 300 350Buffer length (cells)FIGURE 3.11Cell loss ratio with buffer length.4.55 × 10−34Feedback delay = 0AdaptiveOne layerTwo layer w/o trainingTwo layer with training3.5Cell loss ratio32.521.510.50150 200 250 300 350Buffer length (cells)FIGURE 3.12Cell loss ratio with buffer length.
102 Wireless Ad Hoc and Sensor Networksless than the MCR of 3444 cells/sec. The cell losses decrease with anincrease in buffer size for the case of one- and two-layer NNs. Due to aslight decrease in CLR with increasing buffer size, the two-layer NN withtraining method indicates that a buffer size of 150 cells provides a resultsimilar to having buffer size of 350 cells. First of all, low CLR observedfor all methods are due to the feedback, and large buffer size or feedbackimplies that longer delays occur with low CLR.Further, the one-layer and multilayer NN methods render a low CLRcompared to the threshold and adaptive ARMAX methods because theNN approximation property helps to accurately predict the traffic, basedon past measurements. In fact, the two-layer NN method with a prioritraining provides a CLR near zero. The NN-based congestion controllerswere able to achieve the low CLR because the NN accurately predictedtraffic inflow and onset of congestion. Subsequently, the NN controller wasable to generate a desirable source rate to prevent congestion and thesources were able to quickly accommodate their behavior in response tothe delayed feedback. On the other hand, threshold approach generates amuch higher CLR, compared to other schemes, even when the thresholdvalue is kept at 40%, taking longer to transmit all the cells. Increasing thethreshold value will increase CLR but the delay will be smaller. Similar tothe case of ON/OFF traffic, transmission delays were noticed for all thecontroller schemes and the NN-based scheme was able to transfer theinformation with a delay of less than 2%, whereas others took much longer.Figure 3.13 and Figure 3.14 (same as Figure 3.13, but with thresholdingscheme removed) show the result of the simulated congestion created bythrottling the outgoing transmission link at the network switch when abuffer size of 250 cells was used. Throttling was performed by reducingthe service capacity at the switch to 1920 cells/sec during the time intervalof 66.71 to 100 sec as follows:S r = 4680 cells/sec 0≤t ≤33. 33sec,= 3360 cells/sec= 1920 cells/sec33. 37 ≤t≤66. 66sec,66. 71 ≤t≤100sec,= 3360 cells/sec 100. 04 ≤t≤133. 33sec,(3.33)The CLR for all the methods remains close to 0 when the service capacityis higher than the MCR during the time intervals of 0 to 33.33 sec and133.37 to 167 sec. As expected, the CLR attains a maximum value whenthe service capacity is reduced to less than the MCR of the combined traffic.
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Wireless Ad Hocand SensorNetworksPr
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18. Chaos in Automatic Control, edi
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CRC PressTaylor & Francis Group6000
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Table of Contents1 Background on Ne
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3 Congestion Control in ATM Network
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5.4.2 Distributed Power Controller
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7.3 Adaptive and Distributed Fair S
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9.2.2 Overview.....................
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the number of connections in each l
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y Maheswaran Thiagarajan, and tirel
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2 Wireless Ad Hoc and Sensor Networ
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10 Wireless Ad Hoc and Sensor Netwo
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2BackgroundIn this chapter, we prov
Page 74 and 75: Background 51u(k)x n (k + 1)x n (k)
Page 76 and 77: Background 53with x( 0)being the in
Page 78 and 79: Background 55with tr(.) the matrix
Page 80 and 81: Background 57nGiven a function ft (
Page 82 and 83: Background 592.3.2 Lyapunov Stabili
Page 84 and 85: Background 61as well as Jagannathan
Page 86 and 87: Background 63The subsequent example
Page 88 and 89: Background 65Evaluating this along
Page 90 and 91: Background 67Now, select the feedba
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Page 94 and 95: Background 71L 1 (x)L(x, t)L 0 (x)0
Page 96 and 97: Background 73for some R > 0 such th
Page 98 and 99: Background 75Evaluating the first d
Page 100: Background 77Section 2.4Problem 2.4
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7Distributed Fair Scheduling in Wir
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Distributed Fair Scheduling in Wire
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8Optimized Energy and Delay-Based R
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Optimized Energy and Delay-Based Ro
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9Predictive Congestion Control for
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10Adaptive and Probabilistic Power
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Adaptive and Probabilistic Power Co
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