TY - GEN
T1 - Identifying frequent items in P2P systems
AU - Li, Mei
AU - Lee, Wang Chien
PY - 2008/9/22
Y1 - 2008/9/22
N2 - As peer-to-peer (P2P) systems receive growing acceptance, the need of identifying 'frequent items' in such systems appears in a variety of applications. In this paper, we define the problem of identifying frequent items (IFI) and propose an efficient in-network processing technique, called in-network filtering (netFilter), to address this important fundamental problem. netFilter operates in two phases: 1) candidate filtering: data items are grouped into item groups to obtain aggregates for pruning of infrequent items; and 2) candidate verification: the aggregates for the remaining candidate items are obtained to filter out false frequent items. We address various issues faced in realizing netFilter, including aggregate computation, candidate set optimization, and candidate set materialization. In addition, we analyze the performance of netFilter, derive the optimal setting analytically, and discuss how to achieve the optimal setting in practice. Finally, we validate the effectiveness of netFilter through extensive simulation.
AB - As peer-to-peer (P2P) systems receive growing acceptance, the need of identifying 'frequent items' in such systems appears in a variety of applications. In this paper, we define the problem of identifying frequent items (IFI) and propose an efficient in-network processing technique, called in-network filtering (netFilter), to address this important fundamental problem. netFilter operates in two phases: 1) candidate filtering: data items are grouped into item groups to obtain aggregates for pruning of infrequent items; and 2) candidate verification: the aggregates for the remaining candidate items are obtained to filter out false frequent items. We address various issues faced in realizing netFilter, including aggregate computation, candidate set optimization, and candidate set materialization. In addition, we analyze the performance of netFilter, derive the optimal setting analytically, and discuss how to achieve the optimal setting in practice. Finally, we validate the effectiveness of netFilter through extensive simulation.
UR - http://www.scopus.com/inward/record.url?scp=51849158219&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51849158219&partnerID=8YFLogxK
U2 - 10.1109/ICDCS.2008.78
DO - 10.1109/ICDCS.2008.78
M3 - Conference contribution
AN - SCOPUS:51849158219
SN - 9780769531724
T3 - Proceedings - The 28th International Conference on Distributed Computing Systems, ICDCS 2008
SP - 36
EP - 44
BT - Proceedings - The 28th International Conference on Distributed Computing Systems, ICDCS 2008
T2 - 28th International Conference on Distributed Computing Systems, ICDCS 2008
Y2 - 17 July 2008 through 20 July 2008
ER -