A tool for performance estimation of networked embedded end-systems

Abstract

Networked embedded systems are expected to support adaptive streaming audio/video applications with soft real-time constraints. These systems can be designed in a cost efficient manner only if their architecture exploits the “leads” suggested by clever compile-time performance estimators. However, performance estimation of networked embedded systems is a non-trivial problem. The computational requirements of such systems show statistical variations that stem from several interacting factors. At the slowest time scale, applications can adapt to network bandwidth by configuring the processing functionality of their tasks (e.g. compression parameters). Also, there could be significant execution time variations within a task. Thus, it is tricky to compute the net processing demand of several such applications on a system architecture, especially if the system schedules these applications using prioritized run-time schedulers.