TY - GEN
T1 - A unified data structure of name lookup for NDN data plane
AU - Liu, Miaomiao
AU - Song, Tian
AU - Yang, Yating
AU - Zhang, Beichuan
N1 - Publisher Copyright:
© 2017 Copyright held by the owner/author(s).
PY - 2017/9/26
Y1 - 2017/9/26
N2 - NDN data plane relays name-based packets by maintaining three tables: Content Store, Pending Interest Table and Forwarding Information Base. The three tables require similar but different schemes to be matched and updated in a nearly per-packet fashion, thus individual data structure is required for each table. In this work, we propose a unified data structure of name lookup for all three tables, namely CTrie, aiming at reducing the computational cost from three pipelined lookup rounds down to one unified round. CTrie extends the original Patricia trie to a combinational trie structure built from both component-based and byte-based hierarchical names. We compared CTrie with other approaches in speed and memory. The results show that CTrie runs 3.2 times faster and consumes about 38% memory than the current ones in terms of the whole data plane. CTrie fits for all application scenarios of NDN and especially well for IoT like lightweight-deployed scenarios.
AB - NDN data plane relays name-based packets by maintaining three tables: Content Store, Pending Interest Table and Forwarding Information Base. The three tables require similar but different schemes to be matched and updated in a nearly per-packet fashion, thus individual data structure is required for each table. In this work, we propose a unified data structure of name lookup for all three tables, namely CTrie, aiming at reducing the computational cost from three pipelined lookup rounds down to one unified round. CTrie extends the original Patricia trie to a combinational trie structure built from both component-based and byte-based hierarchical names. We compared CTrie with other approaches in speed and memory. The results show that CTrie runs 3.2 times faster and consumes about 38% memory than the current ones in terms of the whole data plane. CTrie fits for all application scenarios of NDN and especially well for IoT like lightweight-deployed scenarios.
UR - http://www.scopus.com/inward/record.url?scp=85032463426&partnerID=8YFLogxK
U2 - 10.1145/3125719.3132103
DO - 10.1145/3125719.3132103
M3 - Conference contribution
AN - SCOPUS:85032463426
T3 - ICN 2017 - Proceedings of the 4th ACM Conference on Information Centric Networking
SP - 188
EP - 189
BT - ICN 2017 - Proceedings of the 4th ACM Conference on Information Centric Networking
PB - Association for Computing Machinery, Inc
T2 - 4th ACM Conference on Information-Centric Networking, ICN 2017
Y2 - 26 September 2017 through 28 September 2017
ER -