scholarly journals Dual-load Bloom filter: Application for name lookup

2020 ◽  
Vol 151 ◽  
pp. 1-9 ◽  
Author(s):  
Jungwon Lee ◽  
Hayoung Byun ◽  
Hyesook Lim
Keyword(s):  
Bloom Filter ◽  
Name Lookup

Learned Bloom-filter for the efficient name lookup in Information-Centric Networking

2021 ◽  
pp. 103077
Author(s):  
Qingtao Wu ◽  
Qianyu Wang ◽  
Mingchuan Zhang ◽  
Ruijuan Zheng ◽  
Junlong Zhu ◽  
...  
Keyword(s):  
Bloom Filter ◽  
Information Centric Networking ◽  
Name Lookup

scholarly journals Route Prefix Caching Using Bloom Filters in Named Data Networking

2020 ◽  
Vol 10 (7) ◽  
pp. 2226
Author(s):  
Junghwan Kim ◽  
Myeong-Cheol Ko ◽  
Jinsoo Kim ◽  
Moon Sun Shin
Keyword(s):  
Bloom Filter ◽  
Bloom Filters ◽  
Experimental Result ◽  
Named Data Networking ◽  
Next Generation Internet ◽  
Complex Process ◽  
Caching Scheme ◽  
Name Lookup ◽  
Cache Miss ◽  
Data Networking

This paper proposes an elaborate route prefix caching scheme for fast packet forwarding in named data networking (NDN) which is a next-generation Internet structure. The name lookup is a crucial function of the NDN router, which delivers a packet based on its name rather than IP address. It carries out a complex process to find the longest matching prefix for the content name. Even the size of a name prefix is variable and unbounded; thus, the name lookup is to be more complicated and time-consuming. The name lookup can be sped up by using route prefix caching, but it may cause a problem when non-leaf prefixes are cached. The proposed prefix caching scheme can cache non-leaf prefixes, as well as leaf prefixes, without incurring any problem. For this purpose, a Bloom filter is kept for each prefix. The Bloom filter, which is widely used for checking membership, is utilized to indicate the branch information of a non-leaf prefix. The experimental result shows that the proposed caching scheme achieves a much higher hit ratio than other caching schemes. Furthermore, how much the parameters of the Bloom filter affect the cache miss count is quantitatively evaluated. The best performance can be achieved with merely 8-bit Bloom filters and two hash functions.

TB2F: Tree-bitmap and bloom-filter for a scalable and efficient name lookup in Content-Centric Networking

2014 ◽  
Author(s):  
Wei Quan ◽  
Changqiao Xu ◽  
Athanasios V. Vasilakos ◽  
Jianfeng Guan ◽  
Hongke Zhang ◽  
...  
Keyword(s):  
Bloom Filter ◽  
Content Centric Networking ◽  
Name Lookup

Scalable Name Lookup with Adaptive Prefix Bloom Filter for Named Data Networking

2014 ◽  
Vol 18 (1) ◽  
pp. 102-105 ◽  
Author(s):  
Wei Quan ◽  
Changqiao Xu ◽  
Jianfeng Guan ◽  
Hongke Zhang ◽  
Luigi Alfredo Grieco
Keyword(s):  
Bloom Filter ◽  
Named Data Networking ◽  
Name Lookup ◽  
Data Networking

Improved Macro-clusters generation using Top-k shared Micro-clusters in Data Streams

2017 ◽  
Vol 7 (10) ◽  
pp. 52
Author(s):  
LAKSHMI PRANEETHA
Keyword(s):  
Real Time ◽  
Data Streams ◽  
Bloom Filter ◽  
Scientific Applications ◽  
Pruning Algorithm ◽  
Density Data ◽  
Data Points ◽  
Short Time ◽  
Information Streams

Now-a-days data streams or information streams are gigantic and quick changing. The usage of information streams can fluctuate from basic logical, scientific applications to vital business and money related ones. The useful information is abstracted from the stream and represented in the form of micro-clusters in the online phase. In offline phase micro-clusters are merged to form the macro clusters. DBSTREAM technique captures the density between micro-clusters by means of a shared density graph in the online phase. The density data in this graph is then used in reclustering for improving the formation of clusters but DBSTREAM takes more time in handling the corrupted data points In this paper an early pruning algorithm is used before pre-processing of information and a bloom filter is used for recognizing the corrupted information. Our experiments on real time datasets shows that using this approach improves the efficiency of macro-clusters by 90% and increases the generation of more number of micro-clusters within in a short time.

P2P Probabilistic Routing Algorithm Based on Data Copying and Bloom Filter

2011 ◽  
Vol 22 (4) ◽  
pp. 773-781
Author(s):  
Gui-Ming ZHU ◽  
De-Ke GUO ◽  
Shi-Yao JIN
Keyword(s):  
Routing Algorithm ◽  
Bloom Filter ◽  
Probabilistic Routing

ODBF: A P2P Weak State Routing Scheme Based on Operative Decaying Bloom Filter

2012 ◽  
Vol 35 (5) ◽  
pp. 910-917
Author(s):  
Gui-Ming ZHU ◽  
De-Ke GUO ◽  
Shi-Yao JIN
Keyword(s):  
Bloom Filter ◽  
Weak State ◽  
Routing Scheme
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