High-Speed Software Data Plane via Vectorized Packet Processing

2018 ◽  
Vol 56 (12) ◽  
pp. 97-103 ◽  
Author(s):  
David Barach ◽  
Leonardo Linguaglossa ◽  
Damjan Marion ◽  
Pierre Pfister ◽  
Salvatore Pontarelli ◽  
...  
2019 ◽  
Vol 149 ◽  
pp. 187-199 ◽  
Author(s):  
Leonardo Linguaglossa ◽  
Dario Rossi ◽  
Salvatore Pontarelli ◽  
Dave Barach ◽  
Damjan Marjon ◽  
...  

Author(s):  
David Barach ◽  
Leonardo Linguaglossa ◽  
Damjan Marion ◽  
Pierre Pfister ◽  
Salvatore Pontarelli ◽  
...  

Author(s):  
Danilo Cerovic ◽  
Valentin Del Piccolo ◽  
Ahmed Amamou ◽  
Kamel Haddadou ◽  
Guy Pujolle

2019 ◽  
Vol 142 ◽  
pp. 98-110 ◽  
Author(s):  
Shie-Yuan Wang ◽  
Chia-Ming Wu ◽  
Yi-Bing Lin ◽  
Ching-Chun Huang

2021 ◽  
Vol 38 (1-2) ◽  
pp. 1-45
Author(s):  
Georgios P. Katsikas ◽  
Tom Barbette ◽  
Dejan Kostić ◽  
JR. Gerald Q. Maguire ◽  
Rebecca Steinert

Deployment of 100Gigabit Ethernet (GbE) links challenges the packet processing limits of commodity hardware used for Network Functions Virtualization (NFV). Moreover, realizing chained network functions (i.e., service chains) necessitates the use of multiple CPU cores, or even multiple servers, to process packets from such high speed links. Our system Metron jointly exploits the underlying network and commodity servers’ resources: ( i ) to offload part of the packet processing logic to the network, ( ii )  by using smart tagging to setup and exploit the affinity of traffic classes, and ( iii )  by using tag-based hardware dispatching to carry out the remaining packet processing at the speed of the servers’ cores, with zero inter-core communication. Moreover, Metron transparently integrates, manages, and load balances proprietary “blackboxes” together with Metron service chains. Metron realizes stateful network functions at the speed of 100GbE network cards on a single server, while elastically and rapidly adapting to changing workload volumes. Our experiments demonstrate that Metron service chains can coexist with heterogeneous blackboxes, while still leveraging Metron’s accurate dispatching and load balancing. In summary, Metron has ( i )  2.75–8× better efficiency, up to ( ii )  4.7× lower latency, and ( iii )  7.8× higher throughput than OpenBox, a state-of-the-art NFV system.


2021 ◽  
Vol 14 (1) ◽  
pp. 18
Author(s):  
Shoujiang Dang ◽  
Rui Han

In scientific domains such as high-energy particle physics and genomics, the quantity of high-speed data traffic generated may far exceed the storage throughput and be unable to be in time stored in the current node. Cooperating and utilizing multiple storage nodes on the forwarding path provides an opportunity for high-speed data storage. This paper proposes the use of flow entries to dynamically split traffic among selected neighbor nodes to sequentially amortize excess traffic. We propose a neighbor selection mechanism based on the Local Name Mapping and Resolution System, in which the node weights are computed by combing the link bandwidth and node storage capability, and determining whether to split traffic by comparing normalized weight values with thresholds. To dynamically offload traffic among multiple targets, the cooperative storage strategy implemented in a programmable data plane is presented using the relative weights and ID suffix matching. Evaluation shows that our proposed schema is more efficient compared with end-to-end transmission and ECMP in terms of bandwidth usage and transfer time, and is beneficial in big science.


Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2563 ◽  
Author(s):  
Jaehyung Wee ◽  
Jin-Ghoo Choi ◽  
Wooguil Pak

Vehicle-to-Everything (V2X) requires high-speed communication and high-level security. However, as the number of connected devices increases exponentially, communication networks are suffering from huge traffic and various security issues. It is well known that performance and security of network equipment significantly depends on the packet classification algorithm because it is one of the most fundamental packet processing functions. Thus, the algorithm should run fast even with the huge set of packet processing rules. Unfortunately, previous packet classification algorithms have focused on the processing speed only, failing to be scalable with the rule-set size. In this paper, we propose a new packet classification approach balancing classification speed and scalability. It can be applied to most decision tree-based packet classification algorithms such as HyperCuts and EffiCuts. It determines partitioning fields considering the rule duplication explicitly, which makes the algorithm memory-effective. In addition, the proposed approach reduces the decision tree size substantially with the minimal sacrifice of classification performance. As a result, we can attain high-speed packet classification and scalability simultaneously, which is very essential for latest services such as V2X and Internet-of-Things (IoT).


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