Approximate membership queries in streams often require recent-window semantics rather than membership over all items ever seen. This paper studies guarded epoch Bloom filters, a sliding-window alternative to counting and stable Bloom filters.
The structure partitions a fixed bit budget into rotating epochs, inserts only into the current epoch, clears whole segments at epoch boundaries, and keeps one additional guard epoch. This guard yields a deterministic live-window invariant: every item inserted in the last W positions remains represented, while rotation-induced stale retention is bounded by one epoch beyond the target window.
We provide the construction, prove its live-coverage and bounded-staleness properties, derive a false-positive approximation, and include a blocked variant that improves locality by confining probes to one block per epoch. Experiments cover 225 synthetic streaming configurations and 45 configurations from a timestamp-ordered web-server access-log stream. At 14 bits per live item, the guarded epoch filter reduces median synthetic false positives from 0.191 for a four-bit counting Bloom baseline to 0.02225 while preserving zero measured live-key false negatives. The method is not a replacement for exact deletion; it targets systems where bounded stale positives are acceptable but false negatives inside the live window are not.
Blogger's Review: The research presents an innovative approach to tackle the false positive issue in streaming data processing, particularly in real-time systems. With its efficient structure design and experimental validation, it demonstrates significant performance improvements, making it valuable for practical applications in real-world systems.