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

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124 CHAPTER 6. PERFORMANCE MODELING OF EBS - CASE STUDIES 1‘PriceUpdate ! " n‘PriceUpdateN 1‘PriceUpdate 1‘PriceUpdate 1‘PriceUpdateN I3_2 1‘PriceUpdateN HQ I3_1 HQ_PriceUpdateT I3_3 SMs 1‘InventoryInfo 1‘InventoryInfo 1‘InvInfoRegister 1‘InvInfoRegister SMs I4_1 SM_InvMovementQ I4_2 SMs 1‘StatInfoSM 1‘StatInfoSM 1‘StatInfoSM 1‘StatInfoSM SMs I5_1 HQ_SMStatsQ I5_2 HQ 1‘ProdAnnounce ! " n‘ProdAnnounceN I6_2 1‘ProdAnnounce 1‘ProdAnnounce 1‘ProdAnnounceN 1‘ProdAnnounceN HQ I6_1 HQ_ProductAnnouncementT I6_3 SMs 1‘CreditCardHL ! " n‘CreditCardHL_N I7_2 1‘CreditCardHL 1‘CreditCardHL 1‘CreditCardHL_N 1‘CreditCardHL_N HQ I7_1 HQ_CreditCardHotlistT I7_3 SMs Figure 6.3: Models of Interactions 3, 4, 5, 6 and 7 Each of these messages is forwarded by transition I3_3 to place SMs representing the machine hosting the SMs. Interactions 4 to 7 are modeled similarly. We now look at Interactions 1 and 2 whose models are shown in Figures 6.4 and 6.5, respectively. The workflow of the interactions can be traced by following the transitions in the order of their suffixes, i.e., I1_1, I1_2, I1_3, etc. In Interaction 2, the CallForOffers message is sent to a HQ_ProductFamilyT topic where n represents the respective product family. The CallForOffers message is then transformed to x CallForOffersN messages representing the respective notification messages forwarded to the SPs (transition I2_2_FindSubscribers). Each SP sends an offer (Offer message) to the DC and one of the offers is selected by transition I2_6 which takes the x offers as input and generates a purchase order (POrder message) sent to the SP_POrderQ queue. The rest of the workflow is similar to Interaction 1. Mapping of Logical to Physical Resources The case study presented exploits the ability to share queues in multiple queueing places by decoupling the logical (software) and physical (hardware) layers of the modeled system. Therefore, the same logical model of the benchmark interactions can be easily customized to different deployment environments. The results presented in this case study can be seen as a validation
6.2. MODELING SPECJMS2007 125 1‘Order 1‘Order 1‘Order 1‘Order I1_1 DC_OrderQ I1_2 1‘StatInfoOrderDC 1‘StatInfoOrderDC HQ_OrderDCStatsQ HQ I1_5 1‘StatInfoOrderDC 1‘OrderConf 1‘OrderConf 1‘Order SMs 1‘ShipInfo I1_4 1‘ShipInfo SM_OrderConfQ 1‘ShipInfo I1_3 1‘ShipDep DCs 1‘ShipDep I1_7 SM_ShipArrQ DC_ShipDepQ I1_6 1‘ShipInfo 1‘ShipConf 1‘ShipConf 1‘ShipConf I1_8 DC_ShipConfQ I1_9 Figure 6.4: Model of Interaction 1 of the QPN extensions introduced in Section 4.3 to our modeling tools and analysis techniques. By using subnet places to represent the MOM server(s) hosting the individual destinations and the clients (HQ, SMs, DCs and SPs), which exchange messages through the MOM infrastructure, we provide additional flexibility in choosing the level of detail at which the system components are modeled. 6.2.3 Experimental Evaluation Experimental Environment To evaluate the accuracy of the proposed modeling approach, we conducted an experimental analysis of the application in the environment depicted in Figure 5.19. Oracle WebLogic server was used as a JMS server installed on a machine with two quad-core Intel Xeon 2.33 GHz CPUs and 16 GB of main memory. The server was run in a 64-bit JRockit 1.5 JVM with 8GB of heap space. A RAID 0 disk array comprised of four disk drives was used for maximum performance. The WebLogic Server was configured to use a file-based store for persistent messages with a 3.8 GB message buffer. The SPECjms2007 drivers were distributed across three machines: i) one Sun Fire X4440 x64 server with four quad-core Opteron 2.3 GHz CPUs and 64 GB of main memory, ii) one Sun Sparc Enterprise T5120 server with one 8-core T2 1.2 GHz CPU and 32 GB of main memory and iii) one IBM x3850 server with four dual-core Intel Xeon 3.5 GHz CPUs and 16 GB of main memory. All machines were connected to a 1 GBit network. Model Adjustments The first step was to customize the model to our deployment environment. The subnet place corresponding to each destination was mapped to a nested QPN containing three queueing places connected in tandem. The latter represent the network link of the MOM server, the MOM server CPUs and the MOM server I/O subsystem. Given that all destinations are deployed on a single physical server, the three queueing places for each destination were mapped to three central
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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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4.1. MODELING METHODOLOGY FOR EBS 3
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