Wireless Ad Hoc and Sensor Networks

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Predictive Congestion Control for Wireless Sensor Networks 457Queue level (packets)throughput (packets/iteration)2015105q iestimated f outf out00 5 10 15 20 25Time (iteration)FIGURE 9.12Queue utilization and estimation of the outgoing flow.10 packets, the controller parameters k vb = 0.1 and l = 0.001. The actualoutgoing flow is set to 0 packets per iteration at the beginning of simulation,then increased to 2, and later to 6 packets per iteration. Next, theoutgoing flow is decreased to 4 packets per iteration. These outgoing flowvariations can also be viewed as MAC data rate changes, thus providingan indication how the proposed protocol performs in networks that supportmultiple modulation rates.Figure 9.12 illustrates the actual and estimated value of the outgoingflow, together with the queue utilization. The outgoing flow estimationis able to track the actual value, f out . The queue utilization, q i , variesfrom the ideal value when the sudden change in the outgoing flowoccurs, because the outgoing traffic estimation could not predict suchabrupt changes. However, after the sudden change, in just a few iterationsof the algorithm, the queue level has converged to the idealvalue as the estimation scheme quickly detected and accommodatedthe changed bandwidth. Additionally, Figure 9.13 presents the errorin estimation of the outgoing flow, e f , and the error of queue utilization,e bi . The errors are bounded and quickly converge to zero because thescheme adapts to the changed outgoing flow rate. Moreover, in agradual change in the outgoing traffic rate, for example during timeinterval of 10 to 14 iterations, the outgoing flow estimation quicklyadapts to the change, and the estimation error decreases even thoughthe outgoing flow rate continues to increase.
458 Wireless Ad Hoc and Sensor Networks10Buffer occupancy error (packets)throughput estimation error(packets/iteration)50−5e bie f−100 5 10 15 20 25Time (iteration)FIGURE 9.13Queue utilization error and outgoing traffic estimation error.9.5 ConclusionsThis chapter presents a novel predictive congestion control schemewhereby the congestion is mitigated by suitably predicting the backoffinterval of all the nodes based on the current network conditions. Thenetwork conditions include the traffic flow through a given region andchannel state. Simulation results show that the proposed scheme increasesthroughput, network efficiency, and energy conservation. With the additionof a fair scheduling algorithm, the scheme guarantees desired QoSand weighted fairness for all flows even during congestion and fadingchannels. Finally, the proposed scheme provides a hop-by-hop mechanismfor throttling packet flow rate, which will help in mitigating congestion.The convergence analysis is demonstrated by using a Lyapunov-basedanalysis.ReferencesBennett, J.C.R. and Zhang, H., WF2Q: worst-case fair weighted fair queuing,Proceedings of the IEEE INFOCOM, Vol. 1, March 1996, pp. 120–128.Golestani, S.J., A self-clocked fair queuing scheme for broadband applications,Proceedings of the IEEE INFOCOM, Vol. 2, June 1994, pp. 636–646.
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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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100 Wireless Ad Hoc and Sensor Netw
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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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