Proceedings ArticleDOI
Towards high-performance flow-level packet processing on multi-core network processors
Yaxuan Qi,Bo Xu,Fei He,Baohua Yang,Jianming Yu,Jun Li +5 more
- pp 17-26
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TLDR
This paper presents a design of high-performance flow-level packet processing system based on multi-core network processors, and proposes a high performance flow classification algorithm optimized for network processors and an efficient flow state management scheme leveraging memory hierarchy to support large number of concurrent flows.Abstract:
There is a growing interest in designing high-performance network devices to perform packet processing at flow level. Applications such as stateful access control, deep inspection and flow-based load balancing all require efficient flow-level packet processing. In this paper, we present a design of high-performance flow-level packet processing system based on multi-core network processors. Main contribution of this paper includes: a) A high performance flow classification algorithm optimized for network processors; b) An efficient flow state management scheme leveraging memory hierarchy to support large number of concurrent flows; c) Two hardware-optimized order-preserving strategies that preserve internal and external per-flow packet order. Experimental results show that: a) The proposed flow classification algorithm, AggreCuts, outperforms the well-known HiCuts algorithm in terms of classification rate and memory usage; b) The presented SigHash scheme can manage over 10M concurrent flow states on the Intel IXP2850 NP with extremely low collision rate; c) The performance of internal packet order-preserving scheme using SRAM queue-array is about 70% of that of external packet order-preserving scheme realized by ordered-thread execution.read more
Citations
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Proceedings ArticleDOI
Packet Classification Algorithms: From Theory to Practice
TL;DR: Compared to the well-known HiCuts and HSM algorithms, HyperSplit achieves superior performance in terms of classification speed, memory usage and preprocessing time.
Journal ArticleDOI
Deep packet inspection tools and techniques in commodity platforms: Challenges and trends
Rafael Antonello,Stenio Fernandes,Carlos Kamienski,Djamel Sadok,Judith Kelner,István Gódor,Geza Szabo,Tord Westholm +7 more
TL;DR: This paper provides the essential technical background material and examines the current body of research in DPI engines' optimization for commodity platforms to discuss current research challenges and present guidelines for building high performance DPI systems.
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Robust dynamic network traffic partitioning against malicious attacks
TL;DR: Experimental results indicate that the proposed dynamic network traffic partitioning scheme outperforms the conventional ones in terms of packet distribution performance especially robustness against malicious attacks.
Proceedings ArticleDOI
Wire-speed statistical classification of network traffic on commodity hardware
Pedro M. Santiago del Río,Dario Rossi,Francesco Gringoli,Lorenzo Nava,Luca Salgarelli,Javier Aracil +5 more
TL;DR: A software-based traffic classification engine running on commodity multi-core hardware, able to process in real-time aggregates of up to 14.2 Mpps over a single 10 Gbps interface, with significant advance with respect to the current state of the art in terms of achieved classification rates.
References
More filters
Proceedings ArticleDOI
Internet traffic classification using bayesian analysis techniques
Andrew W. Moore,Denis Zuev +1 more
TL;DR: This work applies a Naïve Bayes estimator to categorize traffic by application using samples of well-known traffic to allow the categorization of traffic using commonly available information alone, and demonstrates the high level of accuracy achievable with this estimator.
Proceedings ArticleDOI
BLINC: multilevel traffic classification in the dark
TL;DR: This work presents a fundamentally different approach to classifying traffic flows according to the applications that generate them, based on observing and identifying patterns of host behavior at the transport layer and demonstrates the effectiveness of this approach on three real traces.
Proceedings ArticleDOI
Accurate, scalable in-network identification of p2p traffic using application signatures
TL;DR: In this article, the authors identify the application level signatures by examining some available documentations, and packet-level traces, and then utilize the identified signatures to develop online filters that can efficiently and accurately track the P2P traffic even on high-speed network links.
Proceedings ArticleDOI
Packet classification on multiple fields
Pankaj Gupta,Nick McKeown +1 more
TL;DR: It is found that a simple multi-stage classification algorithm, called RFC (recursive flow classification), can classify 30 million packets per second in pipelined hardware, or one million packetsper second in software.
Journal ArticleDOI
Algorithms for packet classification
Pankaj Gupta,Nick McKeown +1 more
TL;DR: This tutorial describes algorithms that are representative of each category of basic search algorithms, and discusses which type of algorithm might be suitable for different applications.