Wireless Ad Hoc and Sensor Networks

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Congestion Control in ATM Networks and the Internet 97Example 3.3.1: Multiple ON/OFF SourcesTo evaluate the performance of the control schemes in the presence ofON/OFF traffic, network congestion was created by altering the servicecapacity at the destination switch as follows:S r = 48,000 cells/sec, 0 ≤t≤360msec,= 45,000 cells/sec,361 ≤t≤720msec,= 40,000 cells/sec, 721 ≤t≤1080msec,(3.32)= 45,000 cells/sec,1081 ≤t≤1440msec,= 48,000 cells/sec,1441 ≤t≤1800msec.Congestion was created by reducing the service capacity to 40,000 cells/sec (less than the MCR). Figure 3.6 and Figure 3.7 (same as Figure 3.6, butwith threshold scheme removed) show the CLR with time when threshold,adaptive, one-layer, two-layer — with and without offline training-basedCell loss ratio0.0450.040.0350.030.0250.020.015ThresholdAdaptiveOne layerTwo layer w/oTwo layer withBuffer length = 2500.010.0050200 400 600 800 1000 1200 1400 1600 1800Time in msecFIGURE 3.6Cell loss ratio with congestion.
98 Wireless Ad Hoc and Sensor NetworksCell loss ratio1.6 × 10−31.41.210.80.60.4AdaptiveOne layerTwo layer w/o trainingTwo layer with trainingBuffer length = 2500.20200 400 600 800 1000 1200 1400 1600 1800Time in msecFIGURE 3.7Cell loss ratio with congestion.congestion control schemes — were deployed at the network switch withbuffer length of 250 cells. The service capacity at the switch for differentintervals of time is given by Equation 3.32. As expected, the CLR for thethreshold, ARMAX, the one-layer NN method increases as the servicecapacity is decreased, reaches a maximum value when the service capacityis reduced to a small value during the time interval of 721 ≤t≤1080msec.The CLR again decreases as the service capacity is increased toward thePCR of the combined traffic.In contrast, the CLR for the two-layer NN method, with and without apriori training, remains near zero throughout the simulation time, evenwhen the service capacity was reduced to 20,000 cells/sec, which impliesthat the two-layer NN controller performs better than all other methodsduring congestion in controlling the arrival rate of the cells into the destinationbuffer. As all the traffic used was of ON/OFF type, the sourcerates were reduced fairly and quickly using the proposed scheme, resultingin a low CLR. Further, a transmission delay of approximately 25 msec(
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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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Page 72 and 73: 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
Page 92 and 93: Background 69is SISL if and only if
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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4Admission Controller Design for Hi
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Admission Controller Design for Hig
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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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Predictive Congestion Control for W
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10Adaptive and Probabilistic Power
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Adaptive and Probabilistic Power Co
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