By Topic

Range-efficient computation of F0 over massive data streams

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
A. Pavan ; Dept. of Comput. Sci., Iowa State Univ., Ames, IA, USA ; S. Tirthapura

Efficient one-pass computation of F0, the number of distinct elements in a data stream, is a fundamental problem arising in various contexts in databases and networking. We consider the problem of efficiently estimating F0 of a data stream where each element of the stream is an interval of integers. We present a randomized algorithm which gives an (ε, δ) approximation of F0, with the following time complexity (n is the size of the universe of the items): (1) the amortized processing time per interval is O(log1/δ log n/ε). (2) The time to answer a query for F0 is O(log1/δ). The workspace used is O(1/ε2log1/δlogn) bits. Our algorithm improves upon a previous algorithm by Bar-Yossef Kumar and Sivakumar (2002), which requires O(1/ε5log1/δlog5n) processing time per item. Our algorithm can be used to compute the max-dominance norm of a stream of multiple signals, and significantly improves upon the current best bounds due to Cormode and Muthukrishnan (2003). This also provides efficient and novel solutions for data aggregation problems in sensor networks studied by Nath and Gibbons (2004) and Considine et. al. (2004).

Published in:

21st International Conference on Data Engineering (ICDE'05)

Date of Conference:

5-8 April 2005