Performance Modeling and Benchmarking of Event-Based ... - DVS

More documents

Recommendations

Info

126 CHAPTER 6. PERFORMANCE MODELING OF EBS - CASE STUDIES 1‘CallForOffers x‘CallForOffersN I2_2_FindSubscribers 1‘CallForOffers 1‘CallForOffers 1‘CallForOffersN 1‘CallForOffersN I2_1 HQ_ProductFamilyT I2_3 1‘Offer 1‘Offer 1‘Offer 1‘CallForOffersN I2_5 DC_IncomingOffersQ I2_4 x‘Offer 1‘POrder 1‘POrder 1‘POrder I2_6 SP_POrderQ I2_7 1‘POrderConf I2_9 DC_POrderConfQ 1‘POrderConf 1‘POrder DCs 1‘PShipInfo 1‘PShipInfo I2_8 SPs I2_10 DC_PShipArrQ 1‘Invoice 1‘Invoice 1‘Invoice HQ_InvoiceQ I2_11 1‘statInfoShipDC 1‘statInfoShipDC HQ_ShipDCStatsQ I2_13 HQ I2_12 1‘PShipConf 1‘PShipConf 1‘PShipConf SP_PShipConfQ I2_14 Figure 6.5: Model of Interaction 2 queues representing the respective physical resources of the Oracle WebLogic server. The CPUs were modeled using a G/M/n/P S queue where n is the number of CPU cores (in our case n = 8). The network and I/O subsystem were modeled using G/M/1/F CF S queues. The mean message service times at the queues were set according to the message resource demands. The latter were estimated by running the interactions in isolation and measuring the utilization of the respective resources. As to the subnet places corresponding to the client locations (SMs, HQ, DCs and SPs), they were each mapped to a nested QPN containing a single queueing place whose queue represents the CPU of the respective client machine. Since all instances of a given location type were deployed on the same client machine, they were all mapped to the same physical queue. Note that this represents the most typical deployment scenario for SPECjms2007. We used the QPME tool to build and analyze the model [128]. Considered Workload Scenarios We consider several different scenarios that represent different types of messaging workloads. These scenarios stress different aspects of the MOM infrastructure including both workloads
6.2. MODELING SPECJMS2007 127 Sc. 1 Sc. 2 Sc. 3 In Out Overall No. of Msg. P2P - P/T 49.2% 40.7% 44.6% 21.0% - - NP/NT 47.2% 39.0% 42.8% 79.0% - Pub/Sub - PT 1.8% 6.0% 4.1% - 17.0% - NP/NT 1.7% 14.2% 8.5% - 83.0% Overall - PT 51.1% 46.7% 48.7% 21.0% 17.0% - NT/NP 48.9% 53.3% 51.3% 79.0% 83.0% Traffic P2P - P/T 32.2% 29.5% 30.8% 11.0% - - NP/NT 66.6 % 61.0% 63.5% 89.0% - Pub/Sub - PT 0.5% 2.3% 1.6% - 3.0% - NP/NT 0.8% 7.2% 4.1% - 97.0% Overall - PT 32.7% 31.8% 32.4% 11.0% 3.0% - NT/NP 67.3% 68.2% 67.6% 89.0% 97.0% Avg. Size (in KBytes) P2P - P/T 2.13 2.31 - - NP/NT 4.59 5.27 - Pub/Sub - PT 1.11 - 0.24 - NP/NT 1.49 - 1.49 Overall - PT 2.00 2.31 0.24 - NT/NP 3.76 5.27 1.49 For Scenario 2 &3: In = Out. Table 6.3: Scenario Transaction Mix
Page 1:
Performance Modeling and Benchmarki
Page 4 and 5:
priorities. Finally, we validated o
Page 6 and 7:
4.3.4 Tool Extension . . . . . . .
Page 8 and 9:
5.7 Proportions of the Interactions
Page 11 and 12:
List of Acronyms Acronym λ t,k j A
Page 13 and 14:
Acronym SPEC-OSG SPE SPN SQL ST SUT
Page 15 and 16:
Chapter 1 Introduction 1.1 Motivati
Page 17 and 18:
PC Server 310 PC Server 310 PC Serv
Page 19 and 20:
1.3. APPROACH AND CONTRIBUTIONS OF
Page 21 and 22:
1.4. THESIS ORGANIZATION 7 • Stan
Page 23 and 24:
Chapter 2 Background In this chapte
Page 25 and 26:
2.1. EVENT-BASED SYSTEMS 11 is gene
Page 27 and 28:
2.2. TECHNOLOGY PLATFORMS OF EVENT-
Page 29 and 30:
Page 31 and 32:
Page 33 and 34:
Page 35 and 36:
2.3. INTRODUCTION TO QUEUEING PETRI
Page 37 and 38:
2.3. INTRODUCTION TO QUEUEING PETRI
Page 39 and 40:
Chapter 3 Related Work In this chap
Page 41 and 42:
3.2. BENCHMARKING OF EVENT-BASED SY
Page 43 and 44:
3.2. BENCHMARKING OF EVENT-BASED SY
Page 45 and 46:
3.4. CONCLUDING REMARKS 31 hierarch
Page 47 and 48:
Chapter 4 Performance Engineering o
Page 49 and 50:
4.1. MODELING METHODOLOGY FOR EBS 3
Page 51 and 52:
Page 53 and 54:
Page 55 and 56:
Page 57 and 58:
4.2. PERFORMANCE MODELING PATTERN 4
Page 59 and 60:
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
4.3. EXTENSIONS OF QPNS 73 ,-).$%&'
Page 89 and 90: 4.4. CONCLUDING REMARKS 75 Without
Page 91 and 92: Chapter 5 Benchmarking of Event-Bas
Page 93 and 94: 5.1. SPECJMS2007 - A STANDARD BENCH
Page 115 and 116: 5.2. CASE STUDY I: SPECJMS2007 101
Page 125 and 126: 5.3. JMS2009-PS - A PUBLISH /SUBSCR
Page 127 and 128: 5.3. JMS2009-PS - A PUBLISH /SUBSCR
Page 129 and 130: 5.4. CASE STUDY II: JMS2009-PS 115
Page 131 and 132: 5.4. CASE STUDY II: JMS2009-PS 117
Page 133 and 134: Chapter 6 Performance Modeling of E
Page 135 and 136: 6.2. MODELING SPECJMS2007 121 Scena
Page 137 and 138: 6.2. MODELING SPECJMS2007 123 BASE*
Page 139: 6.2. MODELING SPECJMS2007 125 1‘O
Page 143 and 144: 6.2. MODELING SPECJMS2007 129 Perce
Page 145 and 146: 6.2. MODELING SPECJMS2007 131 Serve
Page 147 and 148: 6.3. CONCLUDING REMARKS 133 the mod
Page 149 and 150: Chapter 7 Conclusions and Outlook W
Page 151 and 152: 7.1. ONGOING AND FUTURE WORK 137 JA
Page 153 and 154: 7.1. ONGOING AND FUTURE WORK 139 th
Page 155 and 156: Bibliography [1] J. Abbott, K. B. M
Page 157 and 158: BIBLIOGRAPHY 143 [29] BiCEP Researc
Page 159 and 160: BIBLIOGRAPHY 145 [61] G. Cugola and
Page 161 and 162: BIBLIOGRAPHY 147 [92] R. Henjes, M.
Page 163 and 164: BIBLIOGRAPHY 149 [128] S. Kounev an
Page 165 and 166: BIBLIOGRAPHY 151 [162] Object Compu
Page 167 and 168: BIBLIOGRAPHY 153 [197] K. Sachs, S.
Page 169 and 170: BIBLIOGRAPHY 155 [228] P. Tran, P.
Page 171: Erklärung Hiermit erkläre ich, di
show all

Performance Modeling and Benchmarking of Event-Based ... - DVS

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?