TY - GEN
T1 - Ringed filters for peer-to-peer keyword searching
AU - Sei, Yuichi
AU - Honiden, Shinichi
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - Distributed hash tables (DHTs) are a class of decentralized distributed systems that can efficiently search for objects desired by the user. However, a lot of communication traffic comes from multi-word searches. A lot of work has been done to reduce this traffic by using bloom filters, which are space-efficient probabilistic data structures. There are two kinds of bloom filters: fixed-size and variable-size bloom filters. We cannot use variablesize bloom filters because doing so would mean wasting time to calculating hash values. On the other hand, when using fixed-size bloom filters, all the nodes in a DHT are unable to adjust their false positive rate parameters. Therefore, the reduction of traffic is limited because the best false positive rate differs from one node to another. Moreover, in related works, the authors took only two-word searches into consideration, In this paper, we present a method for determining the best false positive rate for three- or more word searches. We also used a new filter called a ringed filter, in which each node can set the approximately best false positive rate. Experiments showed that the ringed filter was able to greatly reduce the traffic.
AB - Distributed hash tables (DHTs) are a class of decentralized distributed systems that can efficiently search for objects desired by the user. However, a lot of communication traffic comes from multi-word searches. A lot of work has been done to reduce this traffic by using bloom filters, which are space-efficient probabilistic data structures. There are two kinds of bloom filters: fixed-size and variable-size bloom filters. We cannot use variablesize bloom filters because doing so would mean wasting time to calculating hash values. On the other hand, when using fixed-size bloom filters, all the nodes in a DHT are unable to adjust their false positive rate parameters. Therefore, the reduction of traffic is limited because the best false positive rate differs from one node to another. Moreover, in related works, the authors took only two-word searches into consideration, In this paper, we present a method for determining the best false positive rate for three- or more word searches. We also used a new filter called a ringed filter, in which each node can set the approximately best false positive rate. Experiments showed that the ringed filter was able to greatly reduce the traffic.
KW - Bloom filter
KW - Communication traffic
KW - Data structure
KW - Distributed hash table
KW - False positive rate
UR - http://www.scopus.com/inward/record.url?scp=40949109831&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=40949109831&partnerID=8YFLogxK
U2 - 10.1109/ICCCN.2007.4317911
DO - 10.1109/ICCCN.2007.4317911
M3 - Conference contribution
AN - SCOPUS:40949109831
SN - 9781424412518
T3 - Proceedings - International Conference on Computer Communications and Networks, ICCCN
SP - 772
EP - 779
BT - Proceedings of 16th International Conference on Computer Communications and Networks 2007, ICCCN 2007
T2 - 16th International Conference on Computer Communications and Networks 2007, ICCCN 2007
Y2 - 13 August 2007 through 16 August 2007
ER -