Maintaining time-decaying stream aggregates

Authors:
Edith Cohen;Martin J. Strauss
Affiliations:
AT&T Research Labs, 180 Park Avenue, Florham Park, NJ, USA;Departments of Mathematics and EECS, University of Michigan, Ann Arbor, MI, USA
Venue:
Journal of Algorithms
Year:
2006

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Abstract

We formalize the problem of maintaining time-decaying aggregates and statistics of a data stream: the relative contribution of each data item to the aggregate is scaled down by a factor that depends on, and is non-increasing with, elapsed time. Time-decaying aggregates are used in applications where the significance of data items decreases over time. We develop storage-efficient algorithms, and establish upper and lower bounds. Surprisingly, even though maintaining decaying aggregates have become a widely-used tool, our work seems to be the first both to explore it formally and to provide storage-efficient algorithms for important families of decay functions, including polynomial decay.