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Table 8 summarizes the simulation set up that was used to derive performance results.
The second category, theoretical models, attempts to derive performance relationships from mass, momentum, and energy balances.
Firstly, the lack of methods to closely trace the interaction sequences and derive performance measures.
We derive performance measures from the labelled transition semantics as in standard models.
In this section, we derive performance bounds for various cases and compare the performance of different schemes operating in the CoMP scenario.
Balsamo and Marzolla [18] present how UML use case, activity and deployment diagrams can be used to derive performance models based on multichain and multiclass Queuing Networks.
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Based on analytically derived performance models, our evaluation with representative workloads show that offloading processing and performing point-to-point data communication improve performance over centralized architectures.
The curve of the analytically derived performance is lying in between these two.
Moreover, the simulation results matched those from numerical analyses using the derived performance indices.
The derived performance metrics depend on the number of hops and the constituent distributions.
Analytically derived performance results indicate a potential capacity gain when introducing multihop communication.
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