The nom Profit-Maximizing Operating System

67 Pages·2015·2 MB·English

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The nom Profit-Maximizing Operating
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Shmuel (Muli) Ben-Yehuda
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The nom Profit-Maximizing Operating
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i Research Thesis
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Submittedinpartialfulfillmentoftherequirements
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Shmuel (Muli) Ben-Yehuda
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SubmittedtotheSenate
oftheTechnion—IsraelInstituteofTechnology
Iyar5775 Haifa May2015
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This research thesis was done under the supervision of Prof. Dan Tsafrir in the Computer
ScienceDepartment.
Someresultsinthisthesisaswellasresultsthisthesisbuildsonhavebeenpublishedasarticles
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bytheauthorandresearchcollaboratorsinconferencesandjournalsduringthecourseofthe
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author’smaster’sresearchperiod. Themostup-to-dateversionsofthesearticlesare:

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OrnaAgmonBen-Yehuda,MuliBen-Yehuda,AssafSchuster,andDanTsafrir. TheriseofRaaS:The
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- Resource-as-a-Servicecloud. CommunicationsoftheACM(CACM),57(7):76–84,July2014.
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1 NadavAmit,MuliBen-Yehuda,DanTsafrir,andAssafSchuster. vIOMMU:efficientIOMMUemulation.
0 InUSENIXAnnualTechnicalConference(ATC),2011.
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- Orna Agmon Ben-Yehuda, Eyal Posener, Muli Ben-Yehuda, Assaf Schuster, and Ahuva Mu’alem.
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Ginseng: Market-drivenmemoryallocation. InACM/USENIXInternationalConferenceonVirtual
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ExecutionEnvironments(VEE).2014.
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OrnaAgmonBen-Yehuda,MuliBen-Yehuda,AssafSchuster,andDanTsafrir. DeconstructingAmazon

s EC2spotinstancepricing. ACMTransactionsonEconomicsandComputation(TEAC),1(3):16:1,
si September2013.
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h MuliBen-Yehuda,OmerPeleg,OrnaAgmonBen-Yehuda,IgorSmolyar,andDanTsafrir. Thenonkernel:
T Akerneldesignedforthecloud. InAsiaPacificWorkshoponSystems(APSYS),2013.

. AbelGordon,NadavAmit,NadavHar’El,MuliBen-Yehuda,AlexLandau,DanTsafrir,andAssaf
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S Schuster. ELI: Bare-metal performance for I/O virtualization. In ACM Architectural Support for
M. ProgrammingLanguages&OperatingSystems(ASPLOS),2012.
MichaelHines,AbelGordon,MarcioSilva,DilmaDaSilva,KyungDongRyu,andMuliBen-Yehuda.

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Applicationsknowbest:Performance-drivenmemoryovercommitwithGinkgo. InIEEEInternational
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n ConferenceonCloudComputingTechnologyandScience(CloudCom),2011.
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e ACKNOWLEDGEMENTS
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First and foremost, I’d like to thank my amazing wife, friend, co-author, and advisor, Orna
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AgmonBen-Yehuda. Youtaughtmemorethanyouwilleverknow. Second,I’dliketothank
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c myamazingchildren,YaelandZe’ev,whomakeitallworthwhile. Third,I’dliketothankmy
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parents, Yoel and Irit Ben Yehuda, for having kept faith all these years, even when my path
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t meandered. Last,I’dliketothankMichaelFactorandOrranKrieger,whotaughtmewhatit
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p meanstodoresearch.
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Thenomoperatingsystemandthisthesishavebeeninthemakingforalongtime. During
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theyearsIworkedonthem,Ipublishednearlytwentypapersco-authoredwithmanywonderful

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people. I’dliketothankallofthem—ithasbeengreatworkingwithyou!
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ThegenerousfinancialsupportoftheTechnionisgratefullyacknowledged.
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Contents
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C ListofFigures
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Abstract 1

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s AbbreviationsandNotations 3
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1 Introduction 5

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. 2 Motivation 9
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2.1 Dynamicresourcepricingiscoming . . . . . . . . . . . . . . . . . . . . . . . 9

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t 2.2 Dynamicpricingmandateschange . . . . . . . . . . . . . . . . . . . . . . . . 10
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3 Design 11
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a 3.1 Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
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e 3.2 Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
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3.3 CPUandscheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

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c 3.4 Memorymanagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
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e 3.5 I/Odevices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
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S 3.6 Networking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

r 3.7 Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
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u 3.8 Price-awareness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
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4 Economicmodelandutilityofnetworkbandwidth 17
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- 5 Implementation 21

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6.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
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T 6.2 Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
6.3 Whatmakesnomfast? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
6.4 Profit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
6.5 Whatmakesnomprofitable? . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
6.6 Effectofbatchingonthroughputandlatency . . . . . . . . . . . . . . . . . . . 30
6.7 Throughput/latencyParetofrontier . . . . . . . . . . . . . . . . . . . . . . . . 31
7 Discussion 35
8 Relatedwork 37
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9 Conclusionsandfuturework 39
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List of Figures
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1.1 Cloudeconomicmodel: Applicationsruninthecloud. Userspaytheapplicationowner
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fortheservicetheapplicationprovides. Theapplicationownerinturnpaysthecloud
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M providerforthecloudresourcestheapplicationuses(e.g.,networkbandwidth). . . . . 5

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i 3.1 Traditionalkernelstructurecomparedwithnom’skernelstructure. . . . . . . . . . . 12
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T 6.1 memcachedthroughputandlatency . . . . . . . . . . . . . . . . . . . . . . . . 25
. 6.2 nhttpdthroughputandlatency . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
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6.3 NetPIPEthroughputandlatency . . . . . . . . . . . . . . . . . . . . . . . . . . 26
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6.4 memcachedprofit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

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6.7 memcachedprofit: staticvs.adaptivebehavior . . . . . . . . . . . . . . . . . . . 29
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e 6.9 NetPIPEprofit: staticvs.adaptivebehavior . . . . . . . . . . . . . . . . . . . . 30
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6.10 memcachedthroughput(inthemanyusersscenario)andlatency(inthesingleuser

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r 6.12 NetPIPE throughput (in the many users scenario) and latency (in the single user
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ut scenario)asafunctionofbatchingdelay . . . . . . . . . . . . . . . . . . . . . . . 32
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m 6.13 ThememcachedthroughputandlatencyParetofrontier . . . . . . . . . . . . . . . 33
o 6.14 ThenhttpdthroughputandlatencyParetofrontier . . . . . . . . . . . . . . . . . 33
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6.15 TheNetPIPEthroughputandlatencyParetofrontier . . . . . . . . . . . . . . . . 33
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