Energy optimization of security-sensitive mixed-criticality applications for distributed real-time systems

Existing studies on mixed-criticality systems are usually safety-oriented, which seriously ignore the security and energy related requirements. In this paper we are interested in the design of security-sensitive mixed-criticality real-time systems. We first establish the system model to capture security-critical applications in mixed-criticality systems. Higher security-criticality protection always results in significant time and energy overhead in mixed-criticality systems. Thus, this paper proposes a system-level design framework for energy optimization of security-sensitive mixed-criticality system with hard real-time constraints. Since the time complexity of finding optimal solutions grows exponentially as problem size grows, a GA (Genetic Algorithm) based on efficient heuristic algorithm is devised to address the system-level optimization problem. Extensive experiments and a real-life case study have been conducted to show the efficiency of the proposed technique, which can obtain balanced minimal energy consumption while satisfying strict security and timing constraints. The proposed approach can save up to 28.9% energy consumption compared with other three candidates.