ACM Transactions on Computer Systems (TOCS)
nCap: wire-speed packet capture and transmission
E2EMON '05 Proceedings of the End-to-End Monitoring Techniques and Services on 2005. Workshop
RouteBricks: exploiting parallelism to scale software routers
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
PacketShader: a GPU-accelerated software router
Proceedings of the ACM SIGCOMM 2010 conference
High speed network traffic analysis with commodity multi-core systems
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Forwarding path architectures for multicore software routers
Proceedings of the Workshop on Programmable Routers for Extensible Services of Tomorrow
Flexible high performance traffic generation on commodity multi---core platforms
TMA'12 Proceedings of the 4th international conference on Traffic Monitoring and Analysis
Blockmon: a high-performance composable network traffic measurement system
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Blockmon: a high-performance composable network traffic measurement system
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
Wire-speed statistical classification of network traffic on commodity hardware
Proceedings of the 2012 ACM conference on Internet measurement conference
Stream-monitoring with blockmon: convergence of network measurements and data analytics platforms
ACM SIGCOMM Computer Communication Review
High-Performance network traffic processing systems using commodity hardware
DataTraffic Monitoring and Analysis
ClickOS and the art of network function virtualization
NSDI'14 Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation
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Nowadays commodity hardware is offering an ever increasing degree of parallelism (CPUs with more and more cores, NICs with parallel queues). However, most of the existing network monitoring software has not yet been designed with high parallelism in mind. Therefore we designed a novel packet capturing engine, named PFQ, that allows efficient capturing and in---kernel aggregation, as well as connection---aware load balancing. Such an engine is based on a novel lockless queue and allows parallel packet capturing to let the user---space application arbitrarily define its degree of parallelism. Therefore, both legacy applications and natively parallel ones can benefit from such a capturing engine. In addition, PFQ outperforms its competitors both in terms of captured packets and CPU consumption.