Mixed Cryptography Constrained Optimization for Heterogeneous, Multicore, and Distributed Embedded Systems
Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721, USA
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Computers 2018, 7(2), 29; https://doi.org/10.3390/computers7020029
Received: 28 February 2018 / Revised: 11 April 2018 / Accepted: 22 April 2018 / Published: 24 April 2018
(This article belongs to the Special Issue Multi-Core Systems-On-Chips Design and Optimization)
Embedded systems continue to execute computational- and memory-intensive applications with vast data sets, dynamic workloads, and dynamic execution characteristics. Adaptive distributed and heterogeneous embedded systems are increasingly critical in supporting dynamic execution requirements. With pervasive network access within these systems, security is a critical design concern that must be considered and optimized within such dynamically adaptive systems. This paper presents a modeling and optimization framework for distributed, heterogeneous embedded systems. A dataflow-based modeling framework for adaptive streaming applications integrates models for computational latency, mixed cryptographic implementations for inter-task and intra-task communication, security levels, communication latency, and power consumption. For the security model, we present a level-based modeling of cryptographic algorithms using mixed cryptographic implementations. This level-based security model enables the development of an efficient, multi-objective genetic optimization algorithm to optimize security and energy consumption subject to current application requirements and security policy constraints. The presented methodology is evaluated using a video-based object detection and tracking application and several synthetic benchmarks representing various application types and dynamic execution characteristics. Experimental results demonstrate the benefits of a mixed cryptographic algorithm security model compared to using a single, fixed cryptographic algorithm. Results also highlight how security policy constraints can yield increased security strength and cryptographic diversity for the same energy constraint.
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Keywords:
security-driven optimization; heterogeneous multicore systems; mixed cryptographic security model; adaptive system; runtime security optimization; system-level codesign; distributed systems
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MDPI and ACS Style
Nam, H.; Lysecky, R. Mixed Cryptography Constrained Optimization for Heterogeneous, Multicore, and Distributed Embedded Systems. Computers 2018, 7, 29. https://doi.org/10.3390/computers7020029
AMA Style
Nam H, Lysecky R. Mixed Cryptography Constrained Optimization for Heterogeneous, Multicore, and Distributed Embedded Systems. Computers. 2018; 7(2):29. https://doi.org/10.3390/computers7020029
Chicago/Turabian StyleNam, Hyunsuk; Lysecky, Roman. 2018. "Mixed Cryptography Constrained Optimization for Heterogeneous, Multicore, and Distributed Embedded Systems" Computers 7, no. 2: 29. https://doi.org/10.3390/computers7020029
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