Wireless Ad Hoc and Sensor Networks

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Distributed Fair Scheduling in Wireless Ad Hoc and Sensor Networks 323due to the addition of weights being less than 16%. This efficiency valueis acceptable to meet the performance. The IEEE 802.11 MAC protocolrenders 84.8% for the same packet size. It can be observed that the additionaloverhead due to the weight transmission is only about 0.6%. Withvery little increase in transmission and computational overheads, theproposed ADFS protocol is able to achieve significant increase in fairnessand aggregate throughput, as shown in the next section.7.4 Performance EvaluationThe performance of the proposed ADFS protocol was evaluated using NS-2 simulator [5] as an extension to wireless networks. ADFS requires modificationsat both the MAC protocol level and at the interface queue level.The following values were used for all the simulations, unless otherwisespecified: channel bandwidth is taken as 2 Mbps, with α = 09 . ,β =−01 . , SF = 002 . , sum of initial weights of all flows is equal to unity,and ρ is a random variable uniformly distributed in the interval [0.9, 1.1].The AODV routing protocol was used. The constant bit rate (CBR) trafficwas used with flows always backlogged, and the packet size was 584 bytes.Example 7.4.1: Star TopologyTo evaluate the fairness of the proposed ADFS protocol, consider a startopology with 16 wireless nodes transmitting to a destination and theflows from each source have a weight of 1/16.Figure 7.3 represents the throughput/weight (normalized weights) ratiovs. the flows for the star topology with 16 wireless nodes. Ideally, thethroughput to initial weight curve should be a straight line parallel to thex-axis for fair scheduling schemes. It is visible that the ADFS results in afair allocation of bandwidth compared to the 802.11 MAC protocol.Figure 7.4 presents the delay variations for the star topology. Delay variationis calculated as the difference between the end-to-end delays forsuccessive packets received at the destination. It can be observed thatADFS results in minimal delay variations, whereas those of 802.11 MACprotocol are relatively high. Huge delay variations can degrade the QoSof an ad hoc network.The performance of the ADFS protocol was also evaluated for networkswith varying packet sizes and initial weights. The results shown inFigure 7.5 are for a network with star topology having 16 flows. Packetsizes of 584, 328, 400, and 256 are used for different flows. It can be seenthat ADFS achieves fair allocation of bandwidth, even when packets ofdifferent sizes were used. Figure 7.6 depicts the throughput/weight ratiofor the flows having different initial weights. The initial weights of the
324 Wireless Ad Hoc and Sensor Networks150140ADFS802.11130Throughput/weight (Kbps)12011010090807060502 4 6 8 10 12 14 16Source nodeFIGURE 7.3ADFS performance.2.52ADFS802.111.5Delay variation (sec)10.50−0.5−10 10 20 30 40 50 60 70 80 90 100 110PacketsFIGURE 7.4Delay variations.
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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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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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