Scheduling And Resource Allocation In Wireless Sensor Networks

140 Pages·2017·0.76 MB·English

CCiittyy UUnniivveerrssiittyy ooff NNeeww YYoorrkk ((CCUUNNYY))
CCUUNNYY AAccaaddeemmiicc WWoorrkkss
Dissertations, Theses, and Capstone Projects CUNY Graduate Center
2-2014
SScchheedduulliinngg AAnndd RReessoouurrccee AAllllooccaattiioonn IInn WWiirreelleessss SSeennssoorr NNeettwwoorrkkss
Yosef Alayev
Graduate Center, City University of New York
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SCHEDULING AND RESOURCE ALLOCATION IN
WIRELESS SENSOR NETWORKS
by
YOSEF ALAYEV
AdissertationsubmittedtotheGraduateFacultyinComputerScienceinpartialfulfillment
oftherequirementsforthedegreeofDoctorofPhilosophy,
THECITYUNIVERSITYOFNEWYORK
2014
©2014
YOSEFALAYEV
AllRightsReserved
ii
Thismanuscripthasbeenreadandacceptedforthe
GraduateFacultyinComputerScienceinsatisfyingofthe
dissertationrequirementforthedegreeofDoctorofPhilosophy.
AmotzBar-Noy
Date ChairofExaminingCommittee
RobertHaralick
Date ExecutiveOfficer
TheodoreBrown
NosonYanofsky
StathisZachos
SupervisoryCommittee
THECITYUNIVERSITYOFNEWYORK
iii
Abstract
SCHEDULINGANDRESOURCEALLOCATIONINWIRELESSSENSOR
NETWORKS
by
YosefAlayev
Adviser: DoctorAmotzBar-Noy
In computer science and telecommunications, wireless sensor networks are an ac-
tive research area. Each sensor in a wireless sensor network has some pre-defined
or on demand tasks such as collecting or disseminating data. Network resources,
such as broadcast channels, number of sensors, power, battery life, etc., are limited.
Hence, a schedule is required to optimally allocate network resources so as to maxi-
mize some profit or minimize some cost. This thesis focuses on scheduling problems
inthewirelesssensornetworksenvironment. Inparticular,westudythreescheduling
problems in the wireless sensor networks: broadcast scheduling, sensor scheduling
for area monitoring, and content distribution scheduling. For each problem the goal
is to find efficient scheduling algorithms that have good approximation guarantees
andperformwellinpractice.
iv
Acknowledgements
There are a number of people that I want to thank for their help, support, and guidance
duringthecourseofmygraduateworkaswellasthewritingprocessofthisthesis. Firstof
allIwanttothankmygraduatementorandadvisorDr. AmotzBar-Noyforhispatienceand
guidance during this process. He taught me not only about research in computer science,
butalsoaboutbeingaresponsibleandgenerousperson.
I acknowledge and thank all the present members of my Thesis Advisory and Defense
Committee: Theodore Brown, Noson Yanofsky, and Stathis Zachos for their support and
encouragementduringthecourseofmywork.
I want to thank all of my coauthors including Thomas La Porta, Matthew P. Johnson,
Lance Kaplan, Fangfei Chen, Yun Hou, and Kin Leung with whom I had a privilege of
collaborating. Thanksforprovidingvaluablefeedbackaswellastechnicalandintellectual
supportduringthecourseofmystudies.
Additionally,IwanttothankallofmyprofessorsatTheGraduateCenterandatQueens
College,especiallyDr. BojanaObrenicforherencouragementandintellectualsupport.
Ithankmyfamily. ThankyouMomandDadforeverythingthatIamandforgivingme
the tools to build my life. You are always proud of me and believe that I can do anything
that I put my mind to. Thanks to my brother Vadim with his wife Natalie and my brother
Gavrielfortheirmoralsupport.
Finally,IthankmywifeAnnaforhermoralandemotionalsupportandforpushingme
tofinishmygraduatework.
v
Table of Contents
TableofContents vi
ListofTables viii
ListofFigures ix
1 Introduction 1
1.1 SchedulingOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1.1 FormalDefinitions . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.2 Schedulingapplications . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 WirelessSensorNetworks . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 Topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3.1 BroadcastSchedulingofInfo-PagestoSensors . . . . . . . . . . . 6
1.3.2 SingleSensorSchedulingProblemwithRefocusingDelays . . . . 7
1.3.3 ContentDistributionScheduling . . . . . . . . . . . . . . . . . . . 7
1.4 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2 BroadcastingInfo-PagestoSensors:
Efficiencyvs. EnergyConservation 9
2.1 IntroductionandMotivation . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2 RelatedWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.3 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.1 BasicModel: GapDrivenCost . . . . . . . . . . . . . . . . . . . . 14
2.3.2 SensorTypesandModifiedModel . . . . . . . . . . . . . . . . . . 17
2.4 OneSensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.5 LowerBound . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.6 ManySensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.6.1 Heuristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.6.2 SimulationStage . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
vi
2.6.3 VariousExperiments . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.6.4 InsightsfromSimulation . . . . . . . . . . . . . . . . . . . . . . . 42
2.7 ConclusionandFutureWork . . . . . . . . . . . . . . . . . . . . . . . . . 42
3 YouCan’tGetThereFromHere:
SensorSchedulingwithRefocusingDelays 44
3.1 IntroductionandMotivation . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.2 RelatedWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.3.1 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.3.2 DelayConstraints . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.3.3 HardnessandPeriodicity . . . . . . . . . . . . . . . . . . . . . . . 54
3.4 LowerBound . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.5 SpecialCases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.6 Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.7 TestbedArchitecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.7.1 VariousExperiments . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.7.2 InsightsfromSimulation . . . . . . . . . . . . . . . . . . . . . . . 73
3.8 ConclusionandFutureWork . . . . . . . . . . . . . . . . . . . . . . . . . 78
4 Throughput Maximization in Mobile WSN Scheduling with Power Control
andRateSelection 79
4.1 IntroductionandMotivation . . . . . . . . . . . . . . . . . . . . . . . . . 79
4.2 RelatedWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
4.3 ProblemModelsandAlgorithms . . . . . . . . . . . . . . . . . . . . . . . 87
4.3.1 ProblemModels . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
4.3.2 IPFormulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
4.3.3 ProblemSetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.3.4 Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4.4 SimulationandResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
4.4.1 ResultsandInsights . . . . . . . . . . . . . . . . . . . . . . . . . 106
4.5 ConclusionandFutureWork . . . . . . . . . . . . . . . . . . . . . . . . . 111
5 Conclusions 116
5.1 GeneralApproach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
5.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
5.3 FutureDirections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Bibliography 123
vii
List of Tables
2.1 MathematicalprogramforLBofgapsandlisteningmodel. . . . . . . . . . 22
2.2 MathematicalprogramforLBofthemodel. . . . . . . . . . . . . . . . . . 31
3.1 IPformulationforSSSP. . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.2 TransitionmatrixD. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.3 Sevencostscenariosforfoursites. . . . . . . . . . . . . . . . . . . . . . . 68
3.4 Anglesbetweensites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
3.5 ComparisonofIPandGreedyschedulecostsperslot. . . . . . . . . . . . . 71
4.1 IPformulationwithadjustableRatesandPowers. . . . . . . . . . . . . . . 89
4.2 IPformulationwithadjustablePowers. . . . . . . . . . . . . . . . . . . . . 91
4.3 IPFormulationwithadjustableRates. . . . . . . . . . . . . . . . . . . . . 92
viii
List of Figures
2.1 Round-RobinandOriginalGreedy(Strategy1only);λ =2,σ =7,foralli. 38
i i
2.2 Givenα andFixedλ. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.3 Newα andFixedλ. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
2.4 Givenα;λ Increasingwithi;σ = 7foralli. . . . . . . . . . . . . . . . . 39
i i
2.5 Newα;λ Increasingwithi;σ = 7foralli. . . . . . . . . . . . . . . . . 40
i i
2.6 Givenα;λ Decreasingwithi;σ = 7foralli.. . . . . . . . . . . . . . . . 40
i i
2.7 Newα;λ Decreasingwithi;σ = 7foralli. . . . . . . . . . . . . . . . . 41
i i
3.1 Schedulecostplot: twosites. . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.2 Experimentsetup. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
3.3 IPsolutionsforthe7experiments. . . . . . . . . . . . . . . . . . . . . . . 72
3.4 ComparisonofAlgorithms. . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.5 ComparesolutionsofIP(L,21)byvaryingL. . . . . . . . . . . . . . . . . 74
3.6 ComparesolutionsofIP(4,T)andIP(10,T)byvaryingT. . . . . . . . . . 75
4.1 Timewindows: varioustransmissionratesandfixedpower . . . . . . . . . 80
4.2 Timewindows: varioustransmissionratesandtwodifferentpowerlevels . 82
4.3 Time windows: various transmission rates and two different power levels
andtwointerferingmachines . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.4 Power-Controlledthroughputwith1AP . . . . . . . . . . . . . . . . . . . 102
4.5 Power-Controlledthroughputforconvoyand3APs . . . . . . . . . . . . . 103
4.6 Runtimeforconvoyand3APs . . . . . . . . . . . . . . . . . . . . . . . . 104
4.7 Rate-Controlledthroughputwith1AP . . . . . . . . . . . . . . . . . . . . 105
ix