Fishing in poisson streams: Focusing on the whales, ignoring the minnows
Published
Journal Article
This paper describes a low-complexity approach for reconstructing average packet arrival rates and instantaneous packet counts at a router in a communication network, where the arrivals of packets in each flow follow a Poisson process. Assuming that the rate vector of this Poisson process is sparse or approximately sparse, the goal is to maintain a compressed summary of the process sample paths using a small number of counters, such that at any time it is possible to reconstruct both the total number of packets in each flow and the underlying rate vector. We show that these tasks can be accomplished efficiently and accurately using compressed sensing with expander graphs. In particular, the compressive counts are a linear transformation of the underlying counting process by the adjacency matrix of an unbalanced expander. Such a matrix is binary and sparse, which allows for efficient incrementing when new packets arrive. We describe, analyze, and compare two methods that can be used to estimate both the current vector of total packet counts and the underlying vector of arrival rates. ©2010 IEEE.
Full Text
Duke Authors
Cited Authors
- Raginsky, M; Jafarpour, S; Willett, R; Calderbank, R
Published Date
- June 24, 2010
Published In
- 2010 44th Annual Conference on Information Sciences and Systems, Ciss 2010
Digital Object Identifier (DOI)
- 10.1109/CISS.2010.5464841
Citation Source
- Scopus