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

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110 CHAPTER 5. BENCHMARKING OF EVENT-BASED SYSTEMS<br />

CPU Utilization<br />

100<br />

80<br />

60<br />

40<br />

20<br />

0<br />

0 2 4 6 8 10 12 14 16 18 20<br />

# Queues<br />

Exp. 1<br />

Exp. 2<br />

Message Throughput (Msg/sec)<br />

25000<br />

20000<br />

15000<br />

10000<br />

5000<br />

0<br />

0 2 4 6 8 10 12 14 16 18 20<br />

# Queues<br />

Exp. 1<br />

Exp. 2<br />

CPU Time Per Msg (ms)<br />

1<br />

0.8<br />

0.6<br />

0.4<br />

0.2<br />

0<br />

0 2 4 6 8 10 12 14 16 18 20<br />

# Queues<br />

Exp. 1<br />

Exp. 2<br />

CPU Time Per KByte Payload (ms)<br />

1<br />

0.8<br />

0.6<br />

0.4<br />

0.2<br />

0<br />

0 2 4 6 8 10 12 14 16 18 20<br />

# Queues<br />

Exp. 1<br />

Exp. 2<br />

Figure 5.29: Scenarios 1 <strong>and</strong> 2: NPNT vs.<br />

Queues<br />

PT P2P Messaging with Increasing Number <strong>of</strong><br />

5.2.6 Conclusions <strong>of</strong> the SPECjms2007 Case Study<br />

In this section, we presented a case study <strong>of</strong> a leading JMS platform, the WebLogic server, conducting<br />

an in-depth performance analysis <strong>of</strong> the platform under a number <strong>of</strong> different workload<br />

<strong>and</strong> configuration scenarios. We evaluated the server performance for both the point-to-point<br />

<strong>and</strong> publish/subscribe messaging domains studying the effect <strong>of</strong> individual workload characteristics<br />

on the server CPU utilization, the message throughput, the CPU processing time per<br />

message/KByte payload, the message delivery latency, etc. Two groups <strong>of</strong> scenarios were tested.<br />

The first group uses complex workloads based on the st<strong>and</strong>ard horizontal <strong>and</strong> vertical topologies<br />

provided by the benchmark. The second group includes scenarios that focus on specific aspects<br />

<strong>and</strong> features <strong>of</strong> MOM, e.g the overhead <strong>of</strong> persisting messages, the influence <strong>of</strong> the message size,<br />

the effect <strong>of</strong> increasing the number <strong>of</strong> message producers/consumers <strong>and</strong> the maximum throughput<br />

that can be processed through a given number <strong>of</strong> queues. In most cases, the system scaled<br />

in a linear fashion <strong>and</strong> did not exhibit any unexpected behavior. Interesting observations are the<br />

relation between the number <strong>of</strong> the producer threads <strong>and</strong> message throughput, the number <strong>of</strong><br />

topic consumers <strong>and</strong> CPU load, <strong>and</strong> the influence <strong>of</strong> pub/sub <strong>and</strong> P2P messaging in the vertical<br />

scenario.<br />

5.3 jms2009-PS - A Publish /Subscribe Benchmark<br />

While SPECjms2007 includes some limited publish/subscribe communication as part <strong>of</strong> the<br />

workload, the focus <strong>of</strong> the benchmark is on point-to-point communication via queues which<br />

dominate the overall system workload. Moreover, the SPECjms2007 workload implementation

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