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

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128 CHAPTER 6. PERFORMANCE MODELING OF EBS - CASE STUDIES SPECjms2007 Driver Sun Fire X4440 x64 Server 4 x 4-Core Opteron 8356 2.3 GHz 64 GB RAM, 8x146 GB RAID 10 Debian Linux 2.6.26 Oracle WebLogic Server 10 2 x 4-Core Intel Xeon 2.33 GHz 16 GB RAM, 4 SAS RAID 0 Windows 2003 Server 64bit 1 GBit SPECjms2007 Driver IBM x3850 Server 4 x 2-Core Intel Xeon 3.5 GHz 16 GB, 6 SAS RAID 10 Debian Linux 2.6.26 SPECjms2007 Driver Sun Sparc Enterprise T5120 Server 8-Core T2 1.2 GHz 32 GB RAM, 2x146 GB RAID 0 Solaris 10 10/08 SPARC Figure 6.6: Experimental Environment focused on point-to-point messaging as well as workloads focused on publish/subscribe. In each case, the model was analyzed using SimQPN [127] which took less than 5 minutes. We have intentionally slightly deviated from the standard vertical topology to avoid presenting performance results that may be compared against standard SPECjms2007 results. The latter is prohibited by the SPECjms2007 run and reporting rules. To this end, we use freeform topologies based on the vertical topology with the number of DCs and HQ instances each set to 10. We study the following specific workload scenarios: • Scenario 1: A mix of all seven interactions exercising both P2P and pub/sub messaging. • Scenario 2: A mix of Interactions 4 and 5 focused on P2P messaging. • Scenario 3: A mix of Interactions 3, 6 and 7 focused on pub/sub messaging. In Table 6.3 and Figure 6.7, we provide a detailed workload characterization of the three scenarios to illustrate the differences in terms of transaction mix and message size distribution. Experimental Results Figure 6.8 shows the predicted and measured CPU utilization of the MOM server for the considered customized vertical topology when varying the BASE between 100 and 700. The total number of messages sent and received per second is shown. As we can see, the model predicts the server CPU utilization very accurately as the workload is scaled. To gain a better understanding of the system behavior, we used the model to breakdown the overall utilization among the seven interactions as shown in Table 6.5. The bulk of the load both in terms of message traffic and resulting CPU utilization is produced by Interactions 1 and 5 followed by Interactions 2 and 4. Interactions 3, 6 and 7 which exercise only publish/subscribe messaging produce much
6.2. MODELING SPECJMS2007 129 Percentages of Msg. Count 50 % 40 % 30 % 20 % 10 % 0 % P2P P / T P2P NT / NP Pub/Sub P / T Pub/Sub NP / NT (0,1] (1,2] (2,5] (5,10] (10,20] (20,50] (50,!) (0,1] (1,2] (2,5] (5,10] (10,20] (20,50] (50,!) (0,1] (1,2] (2,5] (5,10] (10,20] (20,50] (50,!) Msg. Size (Kbytes) - Incoming Messages Msg. Size (Kbytes) - Outgoing Messages Msg. Size (Kbytes) - Overall Percentages of Total Traffic 50 % 40 % 30 % 20 % 10 % 0 % P2P P / T P2P NT / NP Pub/Sub P / T Pub/Sub NP / NT (0,1] (1,2] (2,5] (5,10] (10,20] (20,50] (50,!) (0,1] (1,2] (2,5] (5,10] (10,20] (20,50] (50,!) (0,1] (1,2] (2,5] (5,10] (10,20] (20,50] (50,!) Msg. Size (Kbytes) - Incoming Messages Msg. Size (Kbytes) - Outgoing Messages Msg. Size (Kbytes) - Overall (a) Scenario 1 Percentages of Msg. Count 60 % 50 % 40 % 30 % 20 % 10 % 0 % P2P P / T P2P NT / NP (0,1] (1,2] (2,5] (5,10] (10,20] (20,50] (50,!) Msg. Size (Kbytes) - Overall Percentages of Msg. Count 50 % 40 % 30 % 20 % 10 % 0 % Pub/Sub P / T Pub/Sub NT / NP (0,.5] (.5,1.2] (1.2,2] (2,10] (10,!) Msg. Size (Kbytes) - Overall Percentages of Total Traffic 60 % 50 % 40 % 30 % 20 % 10 % 0 % P2P P / T P2P NT / NP (0,1] (1,2] (2,5] (5,10] (10,20] (20,50] (50,!) Msg. Size (Kbytes) - Overall Percentages of Total Traffic 50 % 40 % 30 % 20 % 10 % 0 % Pub/Sub P / T Pub/Sub NT / NP (0,.5] (.5,1.2] (1.2,2] (2,10] (10,!) Msg. Size (Kbytes) - Overall (b) Scenario 2 (c) Scenario 3 Figure 6.7: Distribution of the Message Size
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Performance Modeling and Benchmarki
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priorities. Finally, we validated o
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4.3.4 Tool Extension . . . . . . .
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5.7 Proportions of the Interactions
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List of Acronyms Acronym λ t,k j A
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Acronym SPEC-OSG SPE SPN SQL ST SUT
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Chapter 1 Introduction 1.1 Motivati
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PC Server 310 PC Server 310 PC Serv
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1.3. APPROACH AND CONTRIBUTIONS OF
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1.4. THESIS ORGANIZATION 7 • Stan
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Chapter 2 Background In this chapte
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2.1. EVENT-BASED SYSTEMS 11 is gene
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2.2. TECHNOLOGY PLATFORMS OF EVENT-
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2.3. INTRODUCTION TO QUEUEING PETRI
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2.3. INTRODUCTION TO QUEUEING PETRI
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Chapter 3 Related Work In this chap
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3.2. BENCHMARKING OF EVENT-BASED SY
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3.2. BENCHMARKING OF EVENT-BASED SY
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3.4. CONCLUDING REMARKS 31 hierarch
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Chapter 4 Performance Engineering o
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4.3. EXTENSIONS OF QPNS 73 ,-).$%&'
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4.4. CONCLUDING REMARKS 75 Without
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Page 167 and 168: BIBLIOGRAPHY 153 [197] K. Sachs, S.
Page 169 and 170: BIBLIOGRAPHY 155 [228] P. Tran, P.
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