TY - GEN
T1 - Introducing quasirandomness to computer science
AU - Doerr, Benjamin
PY - 2009/10/16
Y1 - 2009/10/16
N2 - The paradigm of quasirandomness led to dramatic progress in different areas of mathematics, with the invention of quasi-Monte Carlo methods in numerical integration probably being the best known example. In the last two decades, discrete mathematics heavily used quasirandom ideas, leading, e.g., to notions like quasirandom graphs. We feel that it is now time to exploit quasirandomness in computer science. As a first application, we propose and analyze a quasirandom analogue of the classical randomized rumor spreading protocol to disseminate information in networks.
AB - The paradigm of quasirandomness led to dramatic progress in different areas of mathematics, with the invention of quasi-Monte Carlo methods in numerical integration probably being the best known example. In the last two decades, discrete mathematics heavily used quasirandom ideas, leading, e.g., to notions like quasirandom graphs. We feel that it is now time to exploit quasirandomness in computer science. As a first application, we propose and analyze a quasirandom analogue of the classical randomized rumor spreading protocol to disseminate information in networks.
UR - https://www.scopus.com/pages/publications/70349883936
U2 - 10.1007/978-3-642-03456-5_6
DO - 10.1007/978-3-642-03456-5_6
M3 - Conference contribution
AN - SCOPUS:70349883936
SN - 3642034551
SN - 9783642034558
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 99
EP - 111
BT - Efficient Algorithms
A2 - Albers, Susanne
A2 - Alt, Helmut
A2 - Naher, Stefan
ER -