Evaluating Cryptographic Performance of Raspberry Pi Clusters
ARM-based single board computers (SBCs) such as the Raspberry Pi capture the imaginations of hobbyists and scientists due to their low cost and versatility. With the deluge of data produced in edge environments, SBCs and SBC clusters have emerged as low-cost platform for data collection and analysis. Simultaneously, security is a growing concern as new regulations require secure communication for data collected from the edge. In this paper, we compare the performance of a Raspberry Pi cluster to a power-efficient next unit of computing (NUC) and a midrange desktop (MRD) on three leading cryptographic algorithms (AES, Twofish, and Serpent) and assess the general-purpose performance of the three systems using the HPL benchmark. Our results suggest that hardware-level instruction sets for all three cryptographic algorithms should be implemented on single board computers to aid with secure data transfer on the edge.
Computers, Instruction sets, Clustering algorithms, Throughput, Hardware, Encryption, Task analysis
D. Hawthorne, M. Kapralos, R. W. Blaine and S. J. Matthews, "Evaluating Cryptographic Performance of Raspberry Pi Clusters," 2020 IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, USA, 2020, pp. 1-9, doi: 10.1109/HPEC43674.2020.9286247.