Abstract
In this work, authors propose the concept of Protocol Data Unit (PDU) normalization for heterogeneous In-Vehicle Networks (IVN) in automotive gateways (GW). Through the development of the so-called PDU Normalizer Engine (PDUNE), it is possible to create a novel protocol-agnostic frame abstraction layer for PDU and signal gatewaying functions. It consists of normalizing the format of the frames present in the GW ingress ports of any kind (e.g. CAN, LIN, FlexRay or Ethernet). That is, the PDUNE transforms the ingress frames into new refactored frames which are independent of their original network protocol, and this occurs in an early stage before being processed across the different stages of the GW controller till reaching the egress ports, optimizing thus not only the processing itself but also the resources and latencies involved. The hardware (HW) implementation of the PDUNE exploits Software Defined Networking (SDN) architectural concepts by decomposing each ingress frame in two streams: a data frame moving across the data plane and an instruction frame provided with all the necessary metadata that –in parallel and synchronously to the data frame– evolves through the different processing stages of the GW controller performed directly in HW from the control plane. The PDUNE has been synthesized as a coarse-grain configurable HW accelerator (HWA) or co-processor attachable to the system CPU of the GW controller, aimed at contributing towards future automotive zonal GW solutions targeting heterogeneous IVNs with stringent real-time routing and tunneling functional constraints.
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References
Zeng, W., Khalid, M.A., Chowdhury, S.: In-vehicle networks outlook: achievements and challenges. IEEE Commun. Surv. Tutor. 18(3), 1552–1571 (2016)
AUTOSAR. Layered Software architecture (2017). https://www.autosar.org/fileadmin/user_upload/standards/classic/4-3/AUTOSAR_EXP_LayeredSoftwareArchitecture.pdf
Gosda, J.: AUTOSAR - Communication stack. AUTOSAR (2009). https://hpi.de/fileadmin/user_upload/fachgebiete/giese/Ausarbeitungen_AUTOSAR0809/CommunicationStack_gosda.pdf
LIN Consortium. LIN Specification Package - Revision 2.2A (2010). https://www.cs-group.de/wp-content/uploads/2016/11/LIN_Specification_Package_2.2A.pdf
International Organization for Standardization (ISO). ISO 11898 - Road vehicles - Controller Area Network (CAN) (2015). https://www.iso.org/standard/63648.html
BOSCH Gmbh. CAN with Flexible Data-Rate - Specification version 1.0 (2012). https://web.archive.org/web/20151211125301/http://www.bosch-semiconductors.de/media/ubk_semiconductors/pdf_1/canliteratur/can_fd_spec.pdf
FlexRay consortium. FlexRay Communications System - Protocol Specification version 3.0.1 (2010). https://svn.ipd.kit.edu/nlrp/public/FlexRay/FlexRay%E2%84%A2%20Protocol%20Specification%20Version%203.0.1.pdf
OPEN Alliance. Automotive Ethernet Specifications. http://opensig.org/about/specifications/
Halba, K., Mahmoudi, C.: National Institute of Standards and Technology. Gaithersburg, Maryland, USA. In-Vehicle Software Defined Networking: An Enabler for Data Interoperability, Lakeland (2018)
Dr. Andreas Lock, Robert Bosch Gmbh. Trends for future in-vehicle communication (2020)
Crepin, B.T.J.: Intelligente Hardware beschleunigt Ethernet - Data Engine für schnelle Ethernet-Architekturen im Fahrzeug. Automobil Elektronik, no. 4 (2013)
NXP. S32G safe and secure vehicle network processors (2020). https://www.nxp.com/docs/en/fact-sheet/S32G-VEHICLE-NW-FS.pdf
Krishnan, V., Serres, O., Blocksome, M.: Intel Corporation. Configurable Network Protocol Accelerator (2021)
International Organization for Standardization (ISO). ISO-IEC 7498 - Information technology — Open Systems Interconnection — Basic Reference Model (1994). https://www.iso.org/standard/20269.html
Xilinx.DS891-zynq-ultrascale-plus-overview. https://www.xilinx.com/support/documentation/data_sheets/ds891-zynq-ultrascale-plus-overview.pdf
Xilinx. UG573 - UltraScale Architecture Memory Resources User Guide (2020). https://www.xilinx.com/support/documentation/user_guides/ug573-ultrascale-memory-resources.pdf
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Gonzalez Mariño, A., Fons, F., Ming, L., Moreno Arostegui, J.M. (2021). PDU Normalizer Engine for Heterogeneous In-Vehicle Networks in Automotive Gateways. In: Derrien, S., Hannig, F., Diniz, P.C., Chillet, D. (eds) Applied Reconfigurable Computing. Architectures, Tools, and Applications. ARC 2021. Lecture Notes in Computer Science(), vol 12700. Springer, Cham. https://doi.org/10.1007/978-3-030-79025-7_10
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