Performance Modeling and Benchmarking of Event-Based ... - DVS
Performance Modeling and Benchmarking of Event-Based ... - DVS
Performance Modeling and Benchmarking of Event-Based ... - DVS
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4.3. EXTENSIONS OF QPNS 73<br />
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4.3 Extensions <strong>of</strong> QPNs<br />
Figure 4.21: Physical <strong>and</strong> Logical Layers<br />
In this section we discuss how QPNs can be conceptually extended to solve the mentioned shortcomings<br />
<strong>and</strong> limitations <strong>and</strong> to increase modeling simplicity <strong>and</strong> flexibility without increasing<br />
complexity. We propose three extensions for st<strong>and</strong>ard QPNs:<br />
1. Mapping <strong>of</strong> logical to physical resources<br />
• QPNs are extended to support multiple queueing places that share the same physical<br />
queue.<br />
• A flexible mapping <strong>of</strong> logical to physical resources that makes it easy to customize<br />
the model to a specific deployment <strong>of</strong> the application is introduced.<br />
2. Non-constant cardinalities <strong>of</strong> transitions<br />
3. Priority support for transitions<br />
• With transition priorities we introduce a firing hierarchy <strong>and</strong> can control the firing<br />
order <strong>of</strong> transitions effectively.<br />
Our target implementation platform is the SimQPN simulation engine <strong>of</strong> QPME [127, 129,<br />
128]. The concept <strong>of</strong> mappings <strong>of</strong> logical to physical resources is already available in the current<br />
version <strong>of</strong> QPME while both the others are planned for future release.<br />
4.3.1 Mapping <strong>of</strong> Logical to Physical Resources<br />
In traditional QPNs, the physical resources <strong>of</strong> an application in a specific setup are modeled.<br />
In our approach, we introduce a new level <strong>of</strong> indirection to increase flexibility <strong>and</strong> reusability <strong>of</strong><br />
the models by distinguishing between logical layer <strong>and</strong> physical layer (see Figure 4.21).<br />
In our approach the first step is to model the logical relations <strong>of</strong> an application <strong>and</strong> to<br />
focus on the interactions <strong>of</strong> logic entities such as components instead on physical resources such<br />
as CPU. By using subnet places to represent these logical entities, we provide flexibility in<br />
choosing the level <strong>of</strong> detail at which the system components are modeled. Each subnet place is<br />
bound to a nested QPN that may contain multiple queueing places representing logical system<br />
resources available to the respective client or server components, e.g., CPUs, disk subsystems <strong>and</strong>