Reliability-driven deployment optimization for embedded systems

One of the crucial aspects that influence reliability of embedded systems is the deployment of software components to hardware nodes. If the hardware architecture is designed prior to the customized software architecture, which is often the case in product-line manufacturing (e.g. in the automotive domain), the system architect needs to resolve a nontrivial task of finding a (near-)optimal deployment balancing the reliabilities of individual services implemented on the software level.In this paper, we introduce an approach to automate this task. As distinct to related approaches, which typically stay with quantification of reliability for a specific deployment, we target multi-criteria optimization and provide the architect with near-optimal (non-dominated) deployment alternatives with respect to service reliabilities. Toward this goal, we annotate the software and hardware architecture with necessary reliability-relevant attributes, design a method to quantify the quality of individual deployment alternatives, and implement the approach employing an evolutionary algorithm.

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