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

• Published in: Journal of parallel and distributed computing Vol. 133; pp. 377 - 390
• Main Authors: Nam, Hyunsuk, Lysecky, Roman
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.11.2019
• Subjects: Co-design modeling; Design space exploration; Distributed embedded systems; Dynamic optimization; Penalty functions; Security; Distributed embedded systems; Co-design modeling; Penalty functions; Security; Design space exploration; Dynamic optimization
• ISSN: 0743-7315; 1096-0848
• DOI: 10.1016/j.jpdc.2018.02.015

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. •ESL methodology for distributed embedded systems to optimize latency, energy, and security.•Modeling framework integrating computation, communication, cryptographic security levels, and energy.•Employs cryptography for communication between all dataflow tasks, including software and hardware.•Multi-objective optimization method supports security-constrained and security-optimized methods.