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In the burgeoning realm of Internet of Things (IoT) applications on edgedevices, data stream compression has become increasingly pertinent. Theintegration of added compression overhead and limited hardware resources onthese devices calls for a nuanced software-hardware co-design. This paperintroduces CStream, a pioneering framework crafted for parallelizing streamcompression on multicore edge devices. CStream grapples with the distinctchallenges of delivering a high compression ratio, high throughput, lowlatency, and low energy consumption. Notably, CStream distinguishes itself byaccommodating an array of stream compression algorithms, a variety of hardwarearchitectures and configurations, and an innovative set of parallelizationstrategies, some of which are proposed herein for the first time. Ourevaluation showcases the efficacy of a thoughtful co-design involving a lossycompression algorithm, asymmetric multicore processors, and our novel,hardware-conscious parallelization strategies. This approach achieves a 2.8xcompression ratio with only marginal information loss, 4.3x throughput, 65%latency reduction and 89% energy consumption reduction, compared to designslacking such strategic integration.

CStream: Parallel Data Stream Compression on Multicore Edge Devices