Wireless Ad Hoc and Sensor Networks

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Optimized Energy and Delay-Based Routing 39912001000Energy vs network sizeaodvdsrbelloedsrEnergy (mWhr)800600400200040 60 80 100 120Number of nodes140 160FIGURE 8.26Energy consumed with network size.Energy vs network size987aodvdsrbelloedsr6Energy (mWhr)54321040 50 60 70 80 90 100 110 120 130Number of nodes140 150FIGURE 8.27Energy consumed with network size (magnified).
400 Wireless Ad Hoc and Sensor Networks0.70.6Delay vs network sizeaodvdsrbelloedsr0.5Delay (s)0.40.30.20.1040 60 80 100 120Number of nodes140 160FIGURE 8.28Average end-to-end delay with network size.According to Figure 8.28 and Figure 8.29, the average E2E delaysobserved using the OEDSR protocol are much smaller than the delaysincurred using AODV, DSR, and Bellman Ford protocols, because, in theproposed protocol, the E2E delay is considered explicitly in the link_cost_factor calculation. OEDSR ensures that the route renders smaller E2Edelays, whereas the Bellman Ford and the AODV create a route withhigher E2E delay. By contrast, the DSR has much lower E2E delay thanthe Bellman Ford and the AODV protocols. This is because the DSR usessource routing to determine the RNs. Initially, the entire route has to bedetermined prior to routing. However, the OEDSR performs better thanthe DSR, because unlike the DSR, which maintains the same route, theOEDSR changes its route dynamically to lower the E2E delay. Therefore,OEDSR is an on-demand routing protocol.As observed in Figure 8.30 and Figure 8.31, Bellman Ford consumesmore energy, whereas AODV has a greater E2E delay. Therefore, theappropriate overall metric to compare the actual performance of the protocolswill be to take the product of the energy consumed and the averageE2E delay. Both the energy consumed and the average E2E delay have tobe minimized for an optimal routing path. Taking the product of thesetwo metrics helps in identifying the optimal route, and therefore it isconsidered as the overall metric in OEDR. By doing so, it is observed thatthe Bellman Ford routing protocol has the highest product. This is because
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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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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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