The ongoing network softwarization trend holds the promise to revolutionize network infrastructures by making them more flexible, reconfigurable, portable, and more adaptive than ever. Still, the migration from hard-coded/hardwired network functions towards their software-programmable counterparts comes along with the need for tailored optimizations and acceleration techniques, so as to avoid, or at least mitigate, the throughput/latency performance degradation with respect to fixed function network elements. The contribution of this article is twofold. First, we provide a comprehensive overview of the host-based Network Function Virtualization (NFV) ecosystem, covering a broad range of techniques, from low level hardware acceleration and bump-in-the-wire offloading approaches, to highlevel software acceleration solutions, including the virtualization technique itself. Second, we derive guidelines regarding the design, development, and operation of NFV-based deployments that meet the flexibility and scalability requirements of modern communication networks.

We introduce the adaptive cuckoo filter (ACF), a data structure for approximate set membership that extends cuckoo filters by reacting to false positives, removing them for future queries. As an example application, in packet processing queries may correspond to flow identifiers, so a search for an element is likely to be followed by repeated searches for that element. Removing false positives can therefore significantly lower the false-positive rate. The ACF, like the cuckoo filter, uses a cuckoo hash table to store fingerprints. We allow fingerprint entries to be changed in response to a false positive in a manner designed to minimize the effect on the performance of the filter. We show that the ACF is able to significantly reduce the false-positive rate by presenting both a theoretical model for the false-positive rate and simulations using both synthetic data sets and real packet traces.

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Abstract-We introduce a new hardware/software platform for testing SRAM-based FPGAs under heavy-ion and neutron beams, capable of tracing the bit-flips in the configuration memory back to the physical resources affected in the FPGA. The validation was performed using, for the first time, the neutron source at the RAL-ISIS facility. The ISIS beam features a 1/E spectrum, which is similar to the terrestrial one with an acceleration between 10 7 and 10 8 in the energy range 10-100 MeV. The results gathered on Xilinx SRAM-based FPGAs are discussed in terms of cross section and circuit-level modifications.