RasterZip: Compressing network monitoring data with support for partial decompression

Abstract

Network traffic archival solutions are fundamental for a number of emerging applications that require: a) efficient storage of high-speed streams of traffic records and b) support for interactive exploration of massive datasets. Compression is a fundamental building block for any traffic archival solution. However, present solutions are tied to general-purpose compressors, which do not exploit patterns of network traffic data and require to decompress a lot of redundant data for high selectivity queries. In this work we introduce RasterZIP, a novel domain-specific compressor designed for network traffic monitoring data. RasterZIP uses an optimized lossless encoding that exploits patterns of traffic data, like the fact that IP addresses tend to share a common prefix. RasterZIP also introduces a novel decompression scheme that accelerates highly selective queries targeting a small portion of the dataset. With our solution we can achieve high-speed on-the-fly compression of more than half a million traffic records per second. We compare RasterZIP with the fastest Lempel-Ziv-based compressor and show that our solution improves the state-of-the-art both in terms of compression ratios and query response times without introducing penalty in any other performance metric. © 2012 ACM.