Wireless Ad Hoc and Sensor Networks

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Optimized Energy and Delay-Based Routing 42315Throughput vs. packet indexThroughput (packets/sec)1050 0 10 20 30Packet index40 50 60 70FIGURE 8.53Throughput for data rate of 1kbps and 90 bytes per data packet.to note that static routing is not normally preferred because of nodemobility and channel fading.8.11.3 Future WorkFuture work will involve evaluating the proposed protocol in the presenceof node mobility, and channel fading. Additionally, a performance comparisonwith other protocols such as LEACH is planned. Preliminary resultsof the OEDSR hardware implementation, as compared to a static routing,show promise. Future work will include implementation of protocols suchas AODV and DSR on UMR hardware. Comparisons of OEDSR to otherstandard protocols can be shown. Other considerations include larger topologies,differing traffic loads and patterns, and vehicular mobile nodes.8.12 ConclusionsIn this chapter, an OEDR protocol for wireless ad hoc networks is presented.The objective is to develop a fully distributed routing protocol,which finds the optimal routes based on energy-delay costs of the links.The proposed OEDR protocol computes the energy and delay values ofthe links and shares this information with other nodes using the HELLOand TC control messages. Minimizing this product will render the bestpossible route because minimizing energy indicates best possible channelavailable and minimizing delay shows the route selected has maximum
424 Wireless Ad Hoc and Sensor Networksavailable bandwidth. Moreover, it also uses the concept of MPR nodes tominimize the overhead of flooding messages in the network and thenumber of links to be declared. The MPR selection and the routing tablecalculation are performed based on the energy-delay costs of the linksusing a minimum-cost spanning tree algorithm.The performance of the proposed OEDR protocol is presented andanalyzed. The effectiveness of our proposed OEDR protocol was evaluated,using the NS2. The results show that the proposed protocol canachieve smaller delay and better throughput/delay metric. Moreover, theprotocol also results in smaller energy-per-packet and delay product,compared to the OLSR and AODV protocols. Therefore, the proposedOEDR protocol reduces the delay and improves the overall energy-delayefficiency of the network.Next, the OEDSR protocol for WSN is presented. The objective was todevelop a fully distributed routing protocol that finds the optimal routesbased on energy-delay and distance metric, which is used as the link_cost_factor. It could be observed from the results that the path taken from theCH to the BS using the OEDSR is free from loops; it also ensures that theselected route is both energy efficient and has the least E2E delay. Additionally,the lifetime of the network is maximized because the availableenergy is taken into account while selecting nodes to form a route. Moreover,when a node loses more energy, a different path is computed. Clustersare formed only in the subnetwork portion of the network, whereasthe rest of the network is treated as an ad hoc network. Because CH isusually used to route data in a sensor network, the RNs are viewed asCHs in the case of an ad hoc network.The performance of the OEDSR protocol is presented and discussed.The effectiveness of the proposed OEDSR protocol was evaluated usingthe GloMoSim network simulator. The results show that the proposedprotocol achieves smaller average E2E delay, and lower energy consumptionwhen compared with Bellman Ford, DSR, and AODV protocols. TheOEDSR protocol also performs better than OEDR even with node mobilityfor all the performance metrics mentioned earlier.In this chapter, the hardware implementation is also shown for theOEDSR WSN protocol. The objective was to develop a fully distributedrouting protocol that provides optimal routing. The route selection isbased on a metric given by the ratio of energy available and delay multipliedwith distance, which is used as the link cost factor.The OEDSR protocol computes the energy available and average E2Edelay values of the links, and this information along with the distancefrom the BS, determines the best RN. While ensuring that the path fromthe CH to the BS is free from loops, it also ensures that the selected routeis both energy efficient and has the least E2E delay. Additionally, thelifetime of the network is maximized because the energy is taken into
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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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8Optimized Energy and Delay-Based R
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Adaptive and Probabilistic Power Co
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