Channel-Aware Selection of Folded Bloom Filters for Distributed Systems

2026-09-13

AI Summary

研究通过基于信道条件选择OR折叠布隆过滤器，以减少通信受限分布式系统中的传输开销，提高通信效率和接收端数据新鲜度。

Abstract

Periodic Bloom-filter transmission can impose substantial overhead in communication-constrained distributed systems. Lossless compression preserves membership behavior but provides a single transmission size, whereas established OR folding produces smaller representations with higher false-positive rates (FPRs) while preserving the no-false-negative property. This paper investigates channel-aware selection among OR-folded representations. The sender retains an unchanged canonical filter, constructs a catalog satisfying a maximum FPR, and selects the FPR-qualified representation with the largest retained length supported by the communication resources available at each reporting opportunity. Unlike folding driven principally by cardinality and false-positive constraints, selection is driven by time-varying communication conditions. Using two phishing URL datasets, the framework is evaluated under Five-State Markov Capacity, Gilbert--Elliott burst-error, and Rayleigh block-fading models. Channel-aware folding improves communication efficiency and receiver freshness relative to complete-filter and lossless-compression baselines when communication opportunities vary substantially. Under the more favorable Gilbert--Elliott model, it remains competitive in efficiency while maintaining the freshest receiver state. These results show that FPR-qualified folded views provide useful transmission operating points when a recent lower-fidelity update is preferable to delaying a larger representation.

Problem

• Bloom Filters
• Distributed Systems
• Communication Efficiency
• False Positive Rate
• Channel-aware Selection

Innovation

• Channel-aware selection
• OR-folded Bloom Filters
• False-positive rate (FPR)
• Communication efficiency
• Receiver freshness