Wireless Ad Hoc and Sensor Networks

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Distributed Fair Scheduling in Wireless Ad Hoc and Sensor Networks 353Throughput per weight (Kbps)1009080706050403020100Data transmited from clusters802.11DPC + ADF + Sleep0 1 2 3 4 5 6Source cluster idFIGURE 7.29Throughput over weight ratio with flows.random variable uniformly distributed in the interval [0.9, 1.1], and witha delay error limit of 0.1 sec. The fairness is tested in the presence of fadingchannels.Figure 7.29 shows the throughput over weight ratio achieved for each trafficflow in case of standard 802.11 and with the proposed MAC protocol. Theproposed protocol with ADFS scheduling maintains similar throughput perweight ratio (close) for all clusters whereas 802.11 is not. Hence, the proposedprotocol is fair to all sources. Assigning different initial weights to the flowsat each CH will change the throughputs of the flows.7.7 ConclusionsIn this chapter, a novel adaptive and distributed fair scheduling (ADFS)protocol for wireless ad hoc networks is presented. The objective is todevelop a fully distributed fair scheduling algorithm, which meets theoverall QoS. The proposed ADFS protocol uses dynamic adaptation ofthe weights, depending upon the delay experienced, number of packetsin the queue, and the previous weight of the packet. The updated weightsare used in making the scheduling decisions and also in the calculationof the backoff intervals in the CSMA/CA paradigm.The effectiveness of our proposed ADFS protocol was evaluated usingthe NS simulator. The results show that the proposed protocol can achieve
354 Wireless Ad Hoc and Sensor Networksfair allocation of bandwidth with a 10 to 20% increase in throughput andminimum end-to-end delays and delay variations, resulting in a better QoS.Next, the implementation of an ADFS scheme for WSNs is discussed.The objective is to evaluate the hardware capabilities and implementationviability. The results indicate where hardware constraints must be alleviated,thus providing direction for future hardware redesign that meetsthe requirements of the ADFS protocol. More topologies will be utilizedto evaluate the protocol.In the ADFS protocol, weights are updated, and the updated weightsare used in making the scheduling decisions and also in the calculationof the backoff intervals in the CSMA/CA paradigm. Initial weights areassigned to the flows based on the service they expect from the network.The effectiveness of the proposed ADFS protocol was evaluated throughhardware experimentation. The results show that the proposed protocolcan achieve fair allocation of bandwidth with a 13.3% increase in throughput,lower end-to-end delays, and delay variations reduced by 55% (standard),resulting in a better QoS. This shows the ability of the ADFSscheduler to be effectively applied to WSN systems to enhance networkperformance; however, further study is needed to address the current hardwareconstraints and improve overall performance of the implementation.This chapter also introduced the energy-aware and fair protocol forWSNs by taking into account the application considerations. This protocolenables higher throughput in the sensor network and consumesless energy per bit when compared to the standard 802.11. It was demonstratedthat the scheme allows fully DPC and has rendered betterperformance in the presence of radio channel uncertainties. Introductionof sleep mode has not decreased throughput of the network. Moreover,the protocol with the sleep-mode solution uses significantly less transmitterpower per bit compared to 802.11 or the original DPC implementation;hence, the energy is saved and lifetime of sensors extended.Second, the fair scheduling protocol is incorporated that ensures performancein the presence of unusual events for sensor networks. The performanceof the energy-aware scheme consisting of scheduling, DPCwith sleep mode is demonstrated in the presence of fading channels.Simulation results justify theoretical conclusions.ReferencesBennett, J.C.R. and Zhang, H., WF2Q: worst-case fair weighted fair queueing,Proceedings of the IEEE INFOCOM’96, Vol. 1, March 1996, pp. 120–128.Brogan, W.L., Modern Control Theory, 3rd ed., Prentice Hall, NJ, 1991.Demers, A., Keshav, S., and Shenker, S., Analysis and simulation of a fair queuingalgorithm, Proceedings of the IEEE INFOCOM, 2000.
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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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4Admission Controller Design for Hi
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Admission Controller Design for Hig
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Page 326 and 327: 7Distributed Fair Scheduling in Wir
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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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