A Hardware-Conscious Stateful Stream Compression Framework for IoT Applications (Vision)

Xianzhi Zeng, Shuhao Zhang

Abstract: Data stream compression has attracted vast interest in emerging IoT (Internet of Things) applications. However, adopting stream compression on IoT applications is non-trivial due to the divergent demands, i.e., low energy consumption, high throughput, low latency, high compressibility, and tolerable information loss, which sometimes conflict with each other. This is particularly challenging when adopting stateful stream compression algorithms, which rely on states, e.g., a dictionary or model. This paper presents our vision of CStream, a hardware-conscious stateful stream compression framework for IoT applications. Through careful hardware-conscious optimizations, CStream will minimize energy consumption while striving to satisfy the divergent performance demands for parallelizing complex stateful stream compression algorithms for IoT applications.