Simon Schwarzer
ABSTRACT
This paper introduces a new method to predict performance requirements of mobile devices' software tasks using system models describing the hardware and software. With the help of clustering algorithms and linear regression, behavioral models of software tasks are generated automatically. These models are used to project the runtime of representative parts of the software tasks. The runtime of representative execution parts is determined with instruction-accurate simulations which are not feasible for whole executions. The inputs for the projection task a model of the hardware platform and input data parameters, especially the data size. A major advantage of this approach is that the developers do not have to estimate the performance requirements themselves. In this way the method helps to seamlessly integrate the performance analysis process into the development process. The paper introduces the ideas in detail and presents an evaluation of the proposed method for typical software tasks of mobile devices.
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Index Terms
- Automatic estimation of performance requirements for software tasks of mobile devices
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