Wireless Ad Hoc and Sensor Networks

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Congestion Control in ATM Networks and the Internet 1332018TQTCPPower161412102040 60Queue size:(packets)80 100FIGURE 3.28System power with queue size for multiple traffic sources.Figure 3.25 shows the PLR with time when TQ and New-Reno TCP-basedcongestion control schemes were deployed. It can be observed that the PLRfor both schemes increases as the service capacity is decreased, reaches amaximum value when the service capacity is a small value during the timeinterval of 6≤ t < 24sec.The PLR again decreases as the service capacity isincreased. From Figure 3.26, the PLR obtained using TQ congestion controlscheme is much better than the New-Reno TCP congestion control scheme.The complete analysis results are shown in Table 3.5.Figure 3.26 through Figure 3.28 display transmission delay (TD), PLR,and system power (SP), with different queue size for TQ and New-RenoTCP. The packet losses decrease with an increase in queue size for bothschemes. From the three figures, we can see that the TD, PLR, and SPobtained using TQ congestion control scheme is much better than theNew-Reno TCP congestion control scheme.TABLE 3.5TQ vs. New-Reno TCP ComparisonCase II TQ New-Reno TCPPacket loss ratio 0.087% 0.443%Transmission delay 0.2783 0.4110System power 16.5701 11.2162
134 Wireless Ad Hoc and Sensor NetworksExample 3.6.3: Extended TopologyWe also test our scheme’s performance with multiple bottlenecks, usingthe extended topology of Figure 3.19. We use the following traffic sources:3 VBR traffic sources and 3 CBR traffic sources introduced in Case II.Source rates are adjusted using the feedback, uk ( ), separately. The bottleneckbuffer size is taken at 50 packets. For results that are included inFigure 3.29, congestion was created by reducing the bandwidth of differentLinks as follows:Bandwidth of Link0 = 10 to 4 Mbps,Bandwidth of Link1 = 10 to 3 Mbps,Bandwidth of Link2 = 10 to 2 Mbps,Bandwidth of Link3 = 10 to 1 Mbps,t = 3 sec;t = 6 sec;t = 24 sec;t = 27 sec.From Figure 3.29, we can see once again that the PLR obtained usingTQ congestion control scheme is much better than the New-Reno TCPcongestion control scheme because, in the proposed scheme, mathematicalanalysis ensures the convergence and the performance of the scheme. Infact, the PLR using TQ congestion control scheme is equal to zero whilethe transmission delay time is smaller. This is due to the fact that our10.75TQTCPPower0.50.2500 510 15 20 25 30 35Time:(s)40 45 50FIGURE 3.29PLR with time for extended topology.
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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
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Background 51u(k)x n (k + 1)x n (k)
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Background 53with x( 0)being the in
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Background 55with tr(.) the matrix
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Background 57nGiven a function ft (
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Background 592.3.2 Lyapunov Stabili
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Background 61as well as Jagannathan
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Background 63The subsequent example
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Background 65Evaluating this along
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Background 67Now, select the feedba
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Background 69is SISL if and only if
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Background 71L 1 (x)L(x, t)L 0 (x)0
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Background 73for some R > 0 such th
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Background 75Evaluating the first d
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Background 77Section 2.4Problem 2.4
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184 Wireless Ad Hoc and Sensor Netw
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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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Wireless Ad Hoc and Sensor Networks

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