Wireless Ad Hoc and Sensor Networks

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Optimized Energy and Delay-Based Routing 3951310CH 1CH 245811BS61227 913FIGURE 8.24Link cost calculation.CASE II When the CHs have more than one node to relay information,the OEDSR algorithm selection criteria are taken into account. InFigure 8.24, there are two CHs, CH 1 and CH 2 . Each CH sends signals toall the other nodes in the network that are in range. Here, CH 1 first sendsout signals to n 1 , n 3 , n 4 , and n 5 and makes a list on the potential RNs. Thelist is then forwarded to CH 2 . CH 2 checks if it is in range with any of thenodes in the list. Here, n 4 and n 5 are selected as potential common RNs.A single node must be selected from both n 4 and n 5 , based on the highestlink_cost_ factor. The cost to reach n from CH is given by Equation 8.4. So,based on the OEDSR link_cost_ factor, n 4 is selected as the relay node forthe first hop. Next, n 4 sends signals to all the nodes it is in range of, andselects a node as the relay node using the link_cost_ factor. The sameprocedure is carried on until the data is sent to the BS.LEMMA 8.8.1The intermediate nodes on the optimal path are selected as RNs by the previousnodes on the path.PROOF A node is selected as a relay node only if it has the highestlink_cost_ factor and is in range with the previous node on the path.Because OEDSR maximizes the link_cost_ factor, intermediate nodes thatsatisfy the metric on the optimal path are automatically selected as RNs.LEMMA 8.8.2A node can correctly compute the optimal path (lower E2E delay, minimum distanceto the BS and maximum available energy) for the entire network topology.PROOF When selecting the candidate RNs to the CHs, it is ensured thatthe distance from the candidate relay node to the BS is less than the
396 Wireless Ad Hoc and Sensor Networksdistance from the CH to the BS. When calculating the link_cost_ factor,available energy is divided by distance and average E2E delay, to ensurethat the selected nodes are in range with the CHs and close to the BS.This helps minimize the number of MPR nodes in the network.THEOREM 8.8.2OEDSR protocol results in an optimal route (the path with the maximum energy,minimum average E2E delay, and minimum distance from the BS) between theCHs and any source destination.8.9 Performance EvaluationThe OEDSR algorithm is implemented in GloMoSim as a new routingprotocol. Simulations are performed by varying node mobility and numberof network nodes. Additionally, the nodes are made mobile. It isimportant to notice that the OEDSR cannot be directly compared withother hierarchical routing protocols such as LEACH, TEEN, APTEEN, andPEGASIS as these protocols assume that every node is in direct rangewith the BS and, if that is not the case, each node sends a high-powersignal to the BS so that information can be transmitted using one hop.Therefore, OEDR, AODV, DSR, and Bellman Ford’s routing protocol areused for comparison because they use multiple RNs to route informationwhen the BS is not in direct range to a given network node.The total energy consumed and the average E2E delay from a CH tothe BS is minimized by OEDSR and, therefore, those two metrics areconsidered for the analysis. Additionally, the energy available times theaverage E2E delay metric served as a more precise overall metric tocompare the performance of different routing protocols. In Figure 8.25,different network sizes are simulated for the same CH (shown in green)and the same BS (shown in red). It can be seen that when the number ofnodes in the network increases, the OEDSR protocol ensures that theoptimum path is selected for routing the information by selecting theappropriate RNs, which are shown as blue stars. First, the case wherenodes are stationary is discussed.Example 8.9.1: Stationary NodesIt is assumed that the network has stationary nodes that are randomlyplaced on the surface of a structure to monitor incipient faults and otherfaulty events. The simulation was run for networks with 40, 50, 70, 100,and 150 nodes, randomly distributed in an area of size 2000 × 2000 m.Parameters that were used for this simulation include a packet size of
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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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