Wireless Ad Hoc and Sensor Networks

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Optimized Energy and Delay-Based Routing 369StartClear all the entries in RT(s)Is there a node in N(s) forwhich routing table entryis not created?YCompute the fields for therouting table entry from the‘neighbor table’ and enterin the RT(s)Ni = 0i++; New_Entry = NOYIs there a topology table entrywhose last-hop = destinationaddress of a route entry with(distance = i)?YNNew_Entry= YESNEndDoes a route alreadyexists for this destinationYCompute the new cost for the routeCompute the fields for the routing tableentry from the ‘neighbor table’ andenter in the RT(s); New_Entry = YESNIs the new costless than theold cost?Erase the old entry from RT(s)YNFIGURE 8.4Flowchart for the routing table calculation algorithm.
370 Wireless Ad Hoc and Sensor Networkssum: Costs, last−hop+ Clast−hop , destination , and compare with thecost of the old route in the routing table, corresponding tothe same destination address.• If the new cost is less than the old cost, then erase theold entry in the RT()s , and record a new route entry inthe RT()s , with fields for the entry computed similar tostep a.According to the above algorithm, initially start with an empty routingtable for the source node step 1. In step 2, enter routing table entries forall the one-hop neighbors, present in the “neighbor table.” Next (step 3)iterate through the “topology table” to find the entries (destinations) thatare reachable in one hop from a node for which the route has been enteredin the previous iteration (this becomes the new route for the destination).Then check to see if the destination already has an entry in the routingtable. If a routing table entry does not exist for that destination (step 3a),enter the new route in the routing table. Otherwise, if a route alreadyexists to that destination (step 3b), calculate the cost of the new route andcompare with the existing route. If the new cost is less than the old costto reach the destination, then replace the old routing table entry with thenew route. Repeat this process (step 3), until the optimal routes are foundto all the destinations in the network topology. An example is presentednext to illustrate the routing table calculation.Example 8.3.2: Routing Table Algorithm IllustrationTo illustrate the routing table calculation algorithm, consider the networktopology shown in Figure 8.1 and Figure 8.2. Figure 8.5 shows the resultof routing table calculations using the shortest hops method of the OLSRp 2p 15 45p 33 n 1n 2 25 6n 4p 85p 74 67s5n 3n 5 6p4p 5p 6FIGURE 8.5“Shortest hops path” using the OLSR protocol.
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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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Page 342 and 343: Distributed Fair Scheduling in Wire
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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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Wireless Ad Hoc and Sensor Networks

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