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1. Userspace Networking in gem5

   https://doi.org/10.1109/ISPASS61541.2024.00026  

   Umeike, Johnson; Agarwal, Siddharth; Lazarev, Nikita; Alian, Mohammad (May 2024, IEEE)

   Full-system simulation of computer systems is critical for capturing the complex interplay between various hard-ware and software components in future systems. Modeling the network subsystem is indispensable for the fidelity of full-system simulations due to the increasing importance of scale-out systems. Over the last decade, the network software stack has undergone major changes, with userspace networking stacks and data-plane networks rapidly replacing the conventional kernel network stack. Nevertheless, the current state-of-the-art architectural simulator, gem5, still employs kernel networking, which precludes realistic network application scenarios. In this work, we first demonstrate the limitations of gem5's current network stack in achieving high network bandwidth. Then, we enable a userspace networking stack on gem5. We extend gem5's NIC hardware model and device driver to sup-port userspace device drivers running the DPDK framework. Additionally, we implement a network load generator hardware model in gem5 to generate various traffic patterns and per-form per-packet timestamp and latency measurements without introducing packet loss. We develop a suite of six network-intensive benchmarks for stress testing the host network stack. These applications, based on DPDK, can run on both gem5 and real systems. Our experimental results show that enabling userspace networking improves gem5's network bandwidth by 6.3× compared with the current Linux kernel software stack. We characterize the performance of DPDK benchmarks running on both a real system and gem5, and evaluate the sensitivity of the applications to various system and microarchitecture parameters. This work marks the first step in refactoring the networking subsystem in gem5. 

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2. Provenance for Intent-Based Networking

   Ujcich, Benjamin E.; Bates, Adam; Sanders, William H. (January 2020, Proceedings of the IEEE Conference on Network Softwarization)

   Intent-based networking (IBN) promises to simplify the network management and automated orchestration of high-level policies in future networking architectures such as software-defined networking (SDN). However, such abstraction and automation creates new network visibility challenges. Existing SDN network forensics and diagnostics tools operate at a lower level of network abstraction, which makes intent-level reasoning difficult. We present PROVINTENT, a framework extension for SDN control plane tools that accounts for intent semantics. PROVINTENT records the provenance and evolution of intents as the network’s state and apps’ requests change over time and enables reasoning at multiple abstractions. We define an intent provenance model, we implement a proof-of-concept tool, and we evaluate the efficacy of PROVINTENT’s explanatory capabilities by using a representative intent-driven network application. 

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3. Real-Time USB Networking and Device I/O

   https://doi.org/10.1145/3604429  

   West, Richard; Golchin, Ahmad; Njavro, Anton (July 2023, ACM Transactions on Embedded Computing Systems)

   Multicore PC-class embedded systems present an opportunity to consolidate separate microcontrollers as software-defined functions. For instance, an automotive system with more than 100 electronic control units (ECUs) could be replaced with one or, at most, several multicore PCs running software tasks for chassis, body, powertrain, infotainment, and advanced driver assistance system (ADAS) services. However, a key challenge is how to handle real-time device input and output (I/O) and host-level networking as part of sensor data processing and control. A traditional microcontroller would commonly feature one or more Controller Area Network (CAN) buses for real-time I/O. CAN buses are usually absent in PCs, which instead feature higher bandwidth Universal Serial Bus (USB) interfaces. This article shows how to achieve real-time device I/O and host-to-host communication over USB, using suitably written device drivers and a time-aware POSIX-like “tuned pipe” abstraction. This allows developers to establish task pipelines spanning one or more hosts, with end-to-end latency and throughput guarantees for sensor data processing, control, and actuation. 

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4. Autonomy Today: Many Delay-Prone Black Boxes

   https://doi.org/10.4230/LIPICS.ECRTS.2024.12  

   Liu, Sizhe; Wagle, Rohan; Anderson, James H; Yang, Ming; Zhang, Chi; Li, Yunhua (January 2024, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Pellizzoni, Rodolfo (Ed.)

   Machine-learning (ML) technology has been a key enabler in the push towards realizing ever more sophisticated autonomous-driving features. In deploying such technology, the automotive industry has relied heavily on using "black-box" software and hardware components that were originally intended for non-safety-critical contexts, without a full understanding of their real-time capabilities. A prime example of such a component is CUDA, which is fundamental to the acceleration of ML algorithms using NVIDIA GPUs. In this paper, evidence is presented demonstrating that CUDA can cause unbounded task delays. Such delays are the result of CUDA’s usage of synchronization mechanisms in the POSIX thread (pthread) library, so the latter is implicated as a delay-prone component as well. Such synchronization delays are shown to be the source of a system failure that occurred in an actual autonomous vehicle system during testing at WeRide. Motivated by these findings, a broader experimental study is presented that demonstrates several real-time deficiencies in CUDA, the glibc pthread library, Linux, and the POSIX interface of the safety-certified QNX Operating System for Safety. Partial mitigations for these deficiencies are presented and further actions are proposed for real-time researchers and developers to integrate more complete mitigations. 

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5. Blockchain-Enabled Collaborative Intrusion Detection in Software Defined Networks

   Fan, Wenjun; Park, Younghee; Kumar, Shubham; Ganta, Priyatham; Zhou, Xiaobo; Chang, Sang-Yoon Chang (January 2021, IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom))

   null (Ed.)

   Collaborative intrusion detection system (CIDS) shares the critical detection-control information across the nodes for improved and coordinated defense. Software-defined network (SDN) introduces the controllers for the networking control, including for the networks spanning across multiple autonomous systems, and therefore provides a prime platform for CIDS application. Although previous research studies have focused on CIDS in SDN, the real-time secure exchange of the detection relevant information (e.g., the detection signature) remains a critical challenge. In particular, the CIDS research still lacks robust trust management of the SDN controllers and the integrity protection of the collaborative defense information to resist against the insider attacks transmitting untruthful and malicious detection signatures to other participating controllers. In this paper, we propose a blockchain-enabled collaborative intrusion detection in SDN, taking advantage of the blockchain’s security properties. Our scheme achieves three important security goals: to establish the trust of the participating controllers by using the permissioned blockchain to register the controller and manage digital certificates, to protect the integrity of the detection signatures against malicious detection signature injection, and to attest the delivery/update of the detection signature to other controllers. Our experiments in CloudLab based on a prototype built on Ethereum, Smart Contract, and IPFS demonstrates that our approach efficiently shares and distributes detection signatures in real-time through the trustworthy distributed platform. 

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