A Memory-Efficient Hashing by Multi-Predicate Bloom Filters for Packet Classification

2008 ◽  
Author(s):  
H. Yu ◽  
R. Mahapatra
Keyword(s):  
Packet Classification ◽  
Bloom Filters ◽  
Memory Efficient

Accelerating packet classification with counting bloom filters for virtual OpenFlow switching

2018 ◽  
Vol 15 (10) ◽  
pp. 117-128 ◽  
Author(s):  
Jinyuan Zhao ◽  
Zhigang Hu ◽  
Bing Xiong ◽  
Keqin Li
Keyword(s):  
Packet Classification ◽  
Bloom Filters ◽  
Counting Bloom Filters

FMPC: A Fast Multi-Dimensional Packet Classification Algorithm

2014 ◽  
Vol 644-650 ◽  
pp. 3365-3370
Author(s):  
Zhen Hong Guo ◽  
Lin Li ◽  
Qing Wang ◽  
Meng Lin ◽  
Rui Pan
Keyword(s):  
Rapid Development ◽  
Hash Table ◽  
Bloom Filter ◽  
Packet Classification ◽  
Binary Search ◽  
Bloom Filters ◽  
Algorithm Analysis ◽  
Hash Tables ◽  
Worst Case ◽  
Embedded Sram

With the rapid development of the Internet, the number of firewall rules is increasing. The enormous quantity of rules challenges the performance of the packet classification that has already become a bottleneck in firewalls. This dissertation proposes a rapid and multi-dimensional algorithm for packet classification based on BSOL(Binary Search On Leaves), which is named FMPC(FastMulti-dimensional Packet Classification). Different from BSOL, FMPC cuts all dimensions at the same time to decompose rule spaces and stores leaf spaces into hash tables; FMPC constructs a Bloom Filter for every hash table and stores them into embedded SRAM. When classifying a packet, FMPC performs parallel queries on Bloom Filters and determines how to visit hash tables according to the results. Algorithm analysis and the result of simulations show: the average number of hash-table lookups of FMPC is 1 when classifying a packet, which is much smaller than that of BSOL; inthe worst case, the number of hash-table lookups of FMPCisO(logwmax+1⁡), which is also smaller than that of BSOL in multi-dimensional environment, where wmax is the length, in bits, of the dimension whose length is the longest..

scholarly journals A Cache Architecture for Counting Bloom Filters: Theory and Application

2011 ◽  
Vol 2011 ◽  
pp. 1-10
Author(s):  
Mahmood Ahmadi ◽  
Stephan Wong
Keyword(s):  
Mathematical Analysis ◽  
Bloom Filter ◽  
Packet Classification ◽  
Bloom Filters ◽  
Memory Hierarchies ◽  
Cache Architecture ◽  
Multilevel Memory ◽  
Memory Accesses ◽  
Counting Bloom Filter ◽  
Counting Bloom Filters

Within packet processing systems, lengthy memory accesses greatly reduce performance. To overcome this limitation, network processors utilize many different techniques, for example, utilizing multilevel memory hierarchies, special hardware architectures, and hardware threading. In this paper, we introduce a multilevel memory architecture for counting Bloom filters. Based on the probabilities of incrementing of the counters in the counting Bloom filter, a multi-level cache architecture called the cached counting Bloom filter (CCBF) is presented, where each cache level stores the items with the same counters. To test the CCBF architecture, we implement a software packet classifier that utilizes basic tuple space search using a 3-level CCBF. The results of mathematical analysis and implementation of the CCBF for packet classification show that the proposed cache architecture decreases the number of memory accesses when compared to a standard Bloom filter. Based on the mathematical analysis of CCBF, the number of accesses is decreased by at least 53%. The implementation results of the software packet classifier are at most 7.8% (3.5% in average) less than corresponding mathematical analysis results. This difference is due to some parameters in the packet classification application such as number of tuples, distribution of rules through the tuples, and utilized hashing functions.

scholarly journals Bloomflow: Openflow extensions for memory efficient, scalable multicast with multi-stage bloom filters

2017 ◽  
Vol 110 ◽  
pp. 83-102 ◽  
Author(s):  
A. Craig ◽  
B. Nandy ◽  
I. Lambadaris ◽  
P. Koutsakis
Keyword(s):  
Bloom Filters ◽  
Multi Stage ◽  
Memory Efficient

Memory Efficient Routing Using Bloom Filters in Large Scale Sensor Networks

2015 ◽  
Vol 86 (3) ◽  
pp. 1221-1240 ◽  
Author(s):  
Seyedeh Mahboubeh Sajjadian Amiri ◽  
Hadi Tabatabaee Malazi ◽  
Mahmood Ahmadi
Keyword(s):  
Sensor Networks ◽  
Large Scale ◽  
Bloom Filters ◽  
Memory Efficient
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