New Paper: Accelerating Silent Witness Storage
We propose hardware acceleration for a new edge computing abstraction called a Silent Witness. This abstraction embodies a severe asymmetry in the ease of write versus read operations. Surveillance data from one or more video cameras are continuously encrypted and recorded, but the decrypting, processing, or transmission of that data only occurs under stringent privacy controls. For the new search workloads of such a system, decode-enabled storage alleviates the scalability bottleneck imposed by frequent decoding of data. Our experiments show throughput improvements up to 3.5X for typical search workloads of a Silent Witness.
Satyanarayanan, M., Feng, Z., George, S., Harkes, J., Iyengar, R., Turki, H., & Pillai, P. (2022). Accelerating Silent Witness Storage. IEEE Micro, 42(6), 39-47.