Long-term behavior pattern prediction for peer-to-peer systems

Authors
Song, G.Kim, S.
Issue Date
2013-09
Publisher
IEEE Computer Society
Citation
13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013
Abstract
Though there have been many studies on the behavior of nodes in P2P or distributed systems, most focus on fitting all the nodes into a statistical model. These approaches are not sufficient for a long-term prediction since the longterm behavior often correlates with the time of day or day of the week. In this work we study long-term behavior pattern predictors for individual nodes. We then evaluate the performance of our predictors using real trace data sets. The results show that the behavior patterns are reasonably predictable for a week in advance. ? 2013 IEEE.
ISSN
0000-0000
URI
https://pubs.kist.re.kr/handle/201004/80340
DOI
10.1109/P2P.2013.6688723
Appears in Collections:
KIST Conference Paper > 2013
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML

qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE