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
2015 ◽  
Vol 86 (3) ◽  
pp. 1221-1240 ◽  
Author(s):  
Seyedeh Mahboubeh Sajjadian Amiri ◽  
Hadi Tabatabaee Malazi ◽  
Mahmood Ahmadi

2011 ◽  
Vol 7 (1) ◽  
pp. 28-44 ◽  
Author(s):  
Evgeni Krimer ◽  
Mattan Erez

2014 ◽  
Vol 30 (23) ◽  
pp. 3402-3404 ◽  
Author(s):  
Justin Chu ◽  
Sara Sadeghi ◽  
Anthony Raymond ◽  
Shaun D. Jackman ◽  
Ka Ming Nip ◽  
...  

2016 ◽  
Vol 21 (1) ◽  
pp. 7-23 ◽  
Author(s):  
Vassilios G. Vassilakis ◽  
Liang Wang ◽  
Ioannis D. Moscholios ◽  
Michael D. Logothetis

Abstract Information-Centric Networking (ICN) is an emerging networking technology that has been designed to directly operate on named content/information objects, rather than relying on the knowledge of the content location. According to the ICN principles, a user requests the information object by its name or some other form of object identifier. After that, the ICN system is responsible for finding the particular object and sending it back to the user. Despite a large number of works on ICN in recent years, ICN systems still face security challenges. This is especially true when considering different types of alternative networks, such as the wireless community networks (WCNs). In this work, we explore the applicability of ICN principles in the challenging and unpredictable environments of WCNs. We consider stateless content dissemination using Bloom filters (BFs) and analyze two BF based approaches: the traditional single-stage BF and its generalization, the multi-stage BF. We focus on the security aspects of BF based approaches and in particular on distributed denial of service (DDoS) attacks. Finally, we investigate the attack probability for various system and network parameters, such as the number of hash functions, the BF maximum fill factor, and the number of hops toward the victim node.


2014 ◽  
Author(s):  
Li Song ◽  
Liliana Florea ◽  
Ben Langmead

Lighter is a fast, memory-efficient tool for correcting sequencing errors. Lighter avoids counting k-mers. Instead, it uses a pair of Bloom filters, one holding a sample of the input k-mers and the other holding k-mers likely to be correct. As long as the sampling fraction is adjusted in inverse proportion to the depth of sequencing, Bloom filter size can be held constant while maintaining near-constant accuracy. Lighter is parallelized, uses no secondary storage, and is both faster and more memory-efficient than competing approaches while achieving comparable accuracy.


2011 ◽  
Author(s):  
Jared Hotaling ◽  
Jerry Busemeyer ◽  
Richard Shiffrin

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