Wireless Ad Hoc and Sensor Networks

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Optimized Energy and Delay-Based Routing 401Delay vs network size0.0450.04aodvdsrbelloedsrDelay (s)0.0350.030.025050 60 70 80 90 100 110 120 130Number of nodes140 150FIGURE 8.29Average end-to-end delay with network size (magnified).504540Energy delay vs network sizeaodvdsrbelloedsrEnergy ∗ delay (mWhr-s)3530252015105040 60 80 100 120Number of nodes140 160FIGURE 8.30Energy times average end-to-end delay with network size.
402 Wireless Ad Hoc and Sensor NetworksEnergy ∗ delay vs network size0.20.15aodvdsrbelloedsrEnergy ∗ delay (mWhr-s)0.10.050−0.05−0.1−0.1550 60 70 80 90 100 110 120 130Number of nodes140 150FIGURE 8.31Energy times average end-to-end delay with network size (magnified).Bellman Ford consumes high quantities of energy while transmittinginformation from the CHs to the BS. By contrast, from Figure 8.31, OEDSRhas the lowest product. OEDSR performs better than the other routingprotocols as it takes into account a route that has maximum energy availableand minimum E2E delay while minimizing the number of RNs toeffectively route data from the CHs to the BS.Example 8.9.2: Mobile Base StationFor the networks used in Scenario 1, simulations were run again for a mobileBS. The simulation was run for networks with 40, 50, 70, 100, and 150 nodesrandomly distributed in an area of size 2000 × 2000 m. Parameters that wereused for this simulation include a packet size of 256 B, a simulation time ofone hour, and a two-ray ground propagation model with a path-loss exponentof 4.0. In addition, the transmission powers of all active nodes weretaken as 25 dBm, whereas for the sleep nodes it was set to 5 dBm.Figure 8.32 and Figure 8.33 depict how the RNs were selected evenwhen the BS was in motion. It can be observed that OEDSR adapts to thechanging BS position by identifying an efficient route to the BS, irrespectiveof its position.
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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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Wireless Ad Hoc and Sensor Networks

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