Efficient Lookup Solutions for Named Data Networks
Swetha B.1, S. V. Uma2

1Swetha B., Department of Electronics and Communication, RNS Institute of Technology, Bengaluru (Karnataka), India.

2Dr. S. V. Uma, Department of Electronics and Communication, RNS Institute of Technology, Bengaluru (Karnataka), India.

Manuscript received on 07 December 2019 | Revised Manuscript received on 15 December 2019 | Manuscript Published on 31 December 2019 | PP: 621-626 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10971292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1097.1292S19

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Named Data Networking (NDN) is a fast growing architecture, which is proposed as an alternative to existing IP. NDN allows users to request the data identified by a unique name without any information of the hosting entity. NDN supports in-network caching of contents, multi-path forwarding, and data security. In NDN, packet-forwarding decisions are driven by lookup operations on content name of the NDN packets. An NDN node maintains set of routing tables that aid in forwarding decisions. Forwarding the NDN packets depend on lookup of these NDN tables and performing Longest Prefix Matching (LPM) against these NDN tables. The NDN names are unbounded and of variable length. These features along with large and dynamic NDN tables pose several challenges that include increased memory requirement and delayed lookup operations. To this end, there is a need for an efficient data structure that support fast lookup operations with low memory overhead. Several lookup techniques are proposed in this direction. Traversing trie structures would be slow since every level of trie require a memory access. Hash tables incur additional hash computations on names and suffer from collisions. Bloom filters suffer from false positives and do not support deletions. Improving the performance of these structures can lead to a better lookup solution. This survey paper explores different lookup structures for NDN networks. Performance is measured with respect to lookup rate and memory efficiency.

Keywords: Cache Store (CS), Forwarding Information Base (FIB), Longest Prefix Matching (LPM), Pending Interest Table (PIT).
Scope of the Article: Data Management