Security-aware multi-objective optimization of distributed reconfigurable embedded systems

Abstract

Distributed embedded systems are increasingly prevalent in numerous applications, and with pervasive network access within these systems, security is also a critical design concern. We present a modeling and optimization framework for distributed embedded systems incorporating heterogeneous resources, including single core processor, asymmetric multicore processors, and FPGAs. A dataflow-based modeling framework for streaming applications integrates models for computational latency, cryptographic security levels, communication latency, and power consumption. We utilize a multi-objective genetic optimization algorithm to optimize security subject to constraints for energy consumption and minimum security level. The presented methodology is evaluated using a video-based object detection and tracking application considering several distributed heterogeneous embedded systems architectures.