Song, G. Kim, S. 2024-01-12T06:54:52Z 2024-01-12T06:54:52Z 2022-03-07 2013-09 0000-0000 https://pubs.kist.re.kr/handle/201004/80340 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. English IEEE Computer Society Long-term behavior pattern prediction for peer-to-peer systems Conference 10.1109/P2P.2013.6688723 1 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 US Trento 2013-09-09 13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 - Proceedings 2-s2.0-84893246798