Minimizing revalidation and recertification in evolutionary embedded systems

Abstract

Embedded systems have gained immense importance in various domains and they evolve rapidly driven by the necessity to cope with new emerging technologies and new required functionalities. The requirements of evolving embedded systems are subject to changes, thereby leading to repeated redesigns. In model-driven engineering the application's functional and nonfunctional requirements are specified separately from the underlying execution platform. Scheduling is the process of allocating the services of the application model onto the available resources of the platform model. Due to the continuous changes and updates in evolving embedded systems the rescheduling process becomes a critical challenge, because the output of scheduling can be significantly different even upon small changes. This avalanche effect leads to high effort and cost for recertification and revalidation. The contribution of this paper is a method for incremental scheduling, which minimizes the number of changed resource allocations while also satisfying the application's temporal constraints. The incremental scheduling is realized using Mixed Integer Linear Programming (MILP) and the IBM CPLEX optimizer. The presented results allow to reduce cost for recertification and revalidation compared to state-of-the-art scheduling methods.