Probabilistic counting algorithms for data base applications
Journal of Computer and System Sciences
A linear-time probabilistic counting algorithm for database applications
ACM Transactions on Database Systems (TODS)
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Trajectory sampling for direct traffic observation
IEEE/ACM Transactions on Networking (TON)
Charging from sampled network usage
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
A simple algorithm for finding frequent elements in streams and bags
ACM Transactions on Database Systems (TODS)
Efficient implementation of a statistics counter architecture
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
New directions in traffic measurement and accounting: Focusing on the elephants, ignoring the mice
ACM Transactions on Computer Systems (TOCS)
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Analysis of a Statistics Counter Architecture
HOTI '01 Proceedings of the The Ninth Symposium on High Performance Interconnects
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
A data streaming algorithm for estimating subpopulation flow size distribution
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An improved data stream summary: the count-min sketch and its applications
Journal of Algorithms
Estimating flow distributions from sampled flow statistics
IEEE/ACM Transactions on Networking (TON)
Observations on Cisco sampled NetFlow
ACM SIGMETRICS Performance Evaluation Review - Special issue on the First ACM SIGMETRICS Workshop on Large Scale Network Inference (LSNI 2005)
Design of a novel statistics counter architecture with optimal space and time efficiency
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Approximate frequency counts over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Probabilistic lossy counting: an efficient algorithm for finding heavy hitters
ACM SIGCOMM Computer Communication Review
Counter braids: a novel counter architecture for per-flow measurement
SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Empirical evaluation of hash functions for multipoint measurements
ACM SIGCOMM Computer Communication Review
A resource-minimalist flow size histogram estimator
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Space-Code Bloom Filter for Efficient Per-Flow Traffic Measurement
IEEE Journal on Selected Areas in Communications
An efficient hybrid approach to per-flow state tracking for high-speed networks
Computer Communications
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On today's high-speed backbone network links, measuring per-flow traffic information has become very challenging. Maintaining exact per-flow packet counters on OC-192 or OC-768 links is not practically feasible due to computational and cost constrains. Packet sampling as implemented in today's routers results in large approximation errors. Here, we present Probabilistic Multiplicity Counting (PMC), a novel data structure that is capable of accounting traffic per flow probabilistically. The PMC algorithm is very simple and highly parallelizable, and therefore allows for efficient implementations in software and hardware. At the same time, it provides very accurate traffic statistics. We evaluate PMC with both artificial and real-world traffic data, demonstrating that it outperforms other approaches.