Wireless Ad Hoc and Sensor Networks

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Admission Controller Design for High-Speed Networks 159or bandwidth allocation (Fahmy et al. 1998). The bandwidth at any timeinstant k can be shared fairly among n sources asii( ) = Bw( k),nBw ki=∑1PCRPCRi(4.23)orii( ) = Bw( k),nBw ki=∑1MCRMCRi(4.24)orBw ( k)=iIn ( k)ni=∑1iIn ( k)iBw( k),(4.25)where PCRi, MCRi, and Ini( k)denote the PCR, mean cell rate, and thecurrent intended rate of the source “i,” respectively. By contrast, fairnesscriteria can be used to allocate the bandwidth.4.5 Admission ControlHere the available capacity (bandwidth), congestion indicator, and bufferavailability are utilized to admit new sources while maintaining QoS.Figure 4.4 shows the AC with its peripheral schemes for multimedia highspeednetworks. The AC adopts several inputs: available capacity, availableresource estimator, a congestion indicator, and a target packet/cellloss ratio and outputs a decision signal to indicate acceptance or rejectionof the new source. The available capacity is calculated by subtracting thecurrent bandwidth usage from all existing sources from the maximumavailable bandwidth of the physical link.Available_capacity = Smax − Bwi( k)(4.26)where n is the number of existing sources. This available capacity isassumed to be utilized for admitting new sources. Other call admissioncontrol methods use equivalent-capacity-based algorithm. Theni=∑1
160 Wireless Ad Hoc and Sensor NetworksSource setup requestsPBR/PCRNonlinearBandwidthEstimatorAdaptive controllerNetwork resourcecontroller/schedulerPerformanceevaluationAccept/RejectSource transmissionratePacketlossAdaptiveadmission controllerTrafficAdaptivecongestion controllerDelayPerformanceevaluationQueue lengthRate of changeof queue lengthNetwork informationFIGURE 4.4Adaptive admission controller.equivalent-capacity-based algorithm transforms the traffic characteristics(usually described by three parameters: PBR/PCR, MBR/MCR, and peakpacket/cell duration) of a new source into a unified metric, referred to asthe equivalent bandwidth, to reduce the dependence of the proposed controlmechanism on the traffic type. However, the transformation is based oneither a static relationship or simulation curves.The congestion indicator provides an insight into the congestion in thetransmission links based on the burstiness of the existing traffic, so thatfuture congestion can be avoided when a new source is admitted. CLR isthe feedback provided by the system about its performance, which canbe used to provide a closed-loop control system capable of adjusting itselfto provide a stable and robust operation. Also, the available buffer spaceis used as an input to the controller and is calculated as:ni=∑ i1Available_network_resources = ϕmax− x ( k)(4.27)The network resource estimator keeps track of the available bufferspace at each node/switch fabric. When a new source with a bandwidth
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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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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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