Adaptive real-time scheduling for legacy applications

A remarkable research activity has been carried out in the past few years to support real-time applications by means of appropriate scheduling solutions. For scarcely known or highly dynamic applications, feedback scheduling has emerged as an effective technique to tune the scheduling parameters, based on a run-time monitoring of the timing performance of the application. This technique requires a specialised API for the application and is therefore unfit for legacy applications, for which the source code is not accessible. In this paper, we present an alternative technique, called legacy feedback scheduling (LFS), for feedback based adaptation of the scheduling parameters. LFS does not make any assumption on the programming model of the application and is applicable to legacy applications. Throughout the paper, we carry out a comparison between a well settled technique (called adaptive reservations), which leverages a particular structure for the application, and LFS. The conclusion is that the greater generality and flexibility of the LFS has to be paid in terms of timing performance. However, LFS successfully identifies the ldquoaveragerdquo scheduling parameters needed to sustain a given execution rate.