Summary cache: a scalable wide-area Web cache sharing protocol
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
New directions in traffic measurement and accounting
ACM SIGCOMM Computer Communication Review
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
An improved data stream summary: the count-min sketch and its applications
Journal of Algorithms
Time-Decaying Bloom Filters for Data Streams with Skewed Distributions
RIDE '05 Proceedings of the 15th International Workshop on Research Issues in Data Engineering: Stream Data Mining and Applications
Empirical Evaluation of Hash Functions for PacketID Generation in Sampled Multipoint Measurements
PAM '09 Proceedings of the 10th International Conference on Passive and Active Network Measurement
Measurement data reduction through variation rate metering
INFOCOM'10 Proceedings of the 29th conference on Information communications
Hardware-based "on-the-fly" per-flow scan detector pre-filter
TMA'11 Proceedings of the Third international conference on Traffic monitoring and analysis
Stream-monitoring with blockmon: convergence of network measurements and data analytics platforms
ACM SIGCOMM Computer Communication Review
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Several traffic monitoring applications may benefit from the availability of efficient mechanisms for approximately tracking smoothed time averages rather than raw counts. This paper provides two contributions in this direction. First, our analysis of Time-decaying Bloom filters, formerly proposed data structures devised to perform approximate Exponentially Weighted Moving Averages on streaming data, reveals two major shortcomings: biased estimation when measurements are read in arbitrary time instants, and slow operation resulting from the need to periodically update all the filter's counters at once. We thus propose a new construction, called On-demand Time-decaying Bloom filter, which relies on a continuous-time operation to overcome the accuracy/performance limitations of the original window-based approach. Second, we show how this new technique can be exploited in thedesign of high performance stream-based monitoring applications, by developing VoIPSTREAM, a proof-of-concept real-time analysis version of a formerly proposed system for telemarketing call detection. Our validation results, carried out over real telephony data, show how VoIPSTREAM closely mimics the feature extraction process and traffic analysis techniques implemented in the offline system, at a significantly higher processing speed, and without requiring any storage of per-user call detail records.