Flexible Software-Defined Packet Processing Using Low-Area Hardware

Zolfaghari, Hesam; Rossi, Davide; Cerroni, Walter; Okuhara, Hayate; Raffaelli, Carla; Nurmi, Jari

doi:10.1109/access.2020.2996660

Cited by 13 publications

(5 citation statements)

References 24 publications

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“…Refs. [21,22] also used deep pipelines to implement parsers. Through pipeline iterations, header fields of any length can be effectively analyzed.…”

Section: Related Workmentioning

confidence: 99%

100 Gbps Dynamic Extensible Protocol Parser Based on an FPGA

et al. 2022

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In order to facilitate the transition between networks and the integration of heterogeneous networks, the underlying link design of the current mainstream Information-Centric Networking (ICN) still considers the characteristics of the general network and extends the customized ICN protocol on this basis. This requires that the network transmission equipment can not only distinguish general network packets but also support the identification of ICN-specific protocols. However, traditional network protocol parsers are designed for specific network application scenarios, and it is difficult to flexibly expand new protocol parsing rules for different ICN network architectures. For this reason, we propose a general dynamic extensible protocol parser deployed on FPGA, which supports the real-time update of network protocol parsing rules by configuring extended protocol descriptors. At the same time, the multi-queue protocol management mechanism is adopted to realize the grouping management and rapid parsing of the extended protocol. The results demonstrate that the method can effectively support the protocol parsing of 100 Gbps high-speed network data packets and can dynamically update the protocol parsing rules under ultra-low latency. Compared with the current commercial programmable network equipment, this solution improves the protocol update efficiency by several orders of magnitude and better supports the online updating of network equipment.

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“…Refs. [21,22] also used deep pipelines to implement parsers. Through pipeline iterations, header fields of any length can be effectively analyzed.…”

Section: Related Workmentioning

confidence: 99%

100 Gbps Dynamic Extensible Protocol Parser Based on an FPGA

et al. 2022

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“…We also add an FP32/FP16 Floating Point Unit (FPU) [55] to each core, increasing the area of the cluster to 2.29mm 2 . The processing unit in programmable switches is estimated to occupy up to 140mm 2 in a 28nm FDSOI process [56]. By scaling the area, we set a 180mm 2 target area for our PsPIN unit, and we then assume we can fit ∼64 clusters and the L2 memory in our processing unit area budget.…”

Section: L2mentioning

confidence: 99%

Flare: Flexible In-Network Allreduce

De Sensi,

Di Girolamo,

Ashkboos

et al. 2021

Preprint

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The allreduce operation is one of the most commonly used communication routines in distributed applications. To improve its bandwidth and to reduce network traffic, this operation can be accelerated by offloading it to network switches, that aggregate the data received from the hosts, and send them back the aggregated result. However, existing solutions provide limited customization opportunities and might provide suboptimal performance when dealing with custom operators and data types, with sparse data, or when reproducibility of the aggregation is a concern. To deal with these problems, in this work we design a flexible programmable switch by using as a building block PsPIN, a RISC-V architecture implementing the sPIN programming model. We then design, model, and analyze different algorithms for executing the aggregation on this architecture, showing performance improvements compared to state-of-the-art approaches. CCS CONCEPTS• Networks → In-network processing; • Hardware → Networking hardware; • Computer systems organization → Distributed architectures.

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“…Constraint (11) ensures that computational resources required at node i to perform all VNFs from all sources and all the paths are not exceeded. Constraint (12) finds the primary (i) and backup (j) nodes performing the different VNFs for each source. Constraint (13) ensures that the capacity reserved for the backup node j is greater than or equal to the capacity required to perform primary functions at node i, to ensure reliability against single primary hotel failure.…”

Section: Variable Definitionmentioning

confidence: 99%

“…In this way, the baseband is able to control thousands of cells, increasing both network efficiency through dynamic management of resources to respond to rapid traffic changes. In addition, baseband virtualization through paradigms as Network Functions Virtualization (NFV) and Software-Defined Networking (SDN) introduce agility, flexibility, reliability and security [12]. The application of these paradigms is called network slicing, which allows the coexistence of multiple classes of service with different KPIs within the same physical network.…”

Section: Introductionmentioning

confidence: 99%

Differentiated Protection in 5G Vehicular Networks

Amato

Tonini

Raffaelli

2020

2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)

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Automotive applications need high reliability and service continuity to support self-driving and safety in smart city environments. Suitable allocation of network functions is studied and optimal solutions based on Integer Linear Programming methodology are found. Differentiated reliability concept is applied in the presence of two different 5G classes of service, namely eMBB and URLLC. Saving of processing and bandwidth resources is numerically evaluated by combining service-based shared and dedicated protection in a reference scenario. Scalability aspects of the approach are also discussed.

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Flexible Software-Defined Packet Processing Using Low-Area Hardware

Cited by 13 publications

References 24 publications

100 Gbps Dynamic Extensible Protocol Parser Based on an FPGA

100 Gbps Dynamic Extensible Protocol Parser Based on an FPGA

Flare: Flexible In-Network Allreduce

Differentiated Protection in 5G Vehicular Networks

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