Stateful hardware decompression in networking environment

Compression and Decompression can significantly lower the network bandwidth requirements for common internet traffic. Driven by the demands of an enterprise network intrusion system, this paper defines and examines the requirements of popular dictionary-based decompression in the real-time network processing scenario. In particular, a "stateful" decompression is required that arises out of the packet oriented nature of current networks, where the decompression of the data of a packet depends on the decompressed contents of its preceeding packets composing the same data stream. We propose an effective hardware decompression acceleration engine, which fetches the history data into the accelerator's fast memory on-demand and hides the associated latency by exploring the parallelism of the dictionary-based decompression process. We specify and evaluate various design and implementation options of the fetch-on-demand mechanism, i.e. prefetch most frequently used history, on-accelerator history buffer management, and reuse of fetched history data. Through simulation-based performance study, we show the effectiveness of the proposed mechanism on hiding the overhead of stateful decompression. We further show the effects of the design options and the impact on the overall performance of the network service stack of an intrusion prevension system.