Relevant bibliographies by topics / Programmable Dataplanes

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Programmable Dataplanes'

Author: Grafiati
Published: 8 June 2024
Last updated: 31 July 2025

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Journal articles on the topic "Programmable Dataplanes"

1

Sviridov, German, Marco Bonola, Angelo Tulumello, Paolo Giaccone, Andrea Bianco, and Giuseppe Bianchi. "LOcAl DEcisions on Replicated States (LOADER) in programmable dataplanes: Programming abstraction and experimental evaluation." Computer Networks 184 (January 2021): 107637. http://dx.doi.org/10.1016/j.comnet.2020.107637.

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Misa, Chris. "Designing Traffic Monitoring Systems for Self-Driving Networks." ACM SIGMETRICS Performance Evaluation Review 51, no. 2 (2023): 85–87. http://dx.doi.org/10.1145/3626570.3626602.

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Traffic monitoring is a critical component of self-driving networks. In particular, any system that seeks to automatically manage a network's operation must first be equipped with insights about traffic currently flowing through the network. Typically, dedicated traffic monitoring systems deliver such insights in the form of traffic features to high-level human or automated decision makers. Inspired by the exciting capabilities of programmable dataplanes and the persistent challenges of network management, the research community has focused on improving the flexibility and efficiency of traffi
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Salama, Ramiz, Chadi Altrjman, and Fadi Al-Turjman. "Network Security in Architectures for Software Defined Networking (SDN)." NEU Journal for Artificial Intelligence and Internet of Things 4, no. 1 (2025): 37–44. https://doi.org/10.32955/neuaiit202541960.

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SDN (Software Defined Networking) is a new network design that separates the control and dataplanes, allowing for better network management and centralized control. This decoupling makes networks more programmable, scalable, and flexible, which is critical for meeting the changing requirements of modern digital environments. Although SDN streamlines network administration, it also adds new security risks, such as the possibility of centralized control failures, expanded attack surfaces, and vulnerability to multiple network attack types. SDN architectures must include network security to mitig
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Silva, Rui, Daniel Corujo, José Quevedo, and Rui Aguiar. "In‐network computing—challenges and opportunities." Internet Technology Letters, October 17, 2023. http://dx.doi.org/10.1002/itl2.487.

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AbstractThe rapid growth of new applications with high resource demands leads to the need for more computing power. Datacenter servers may not be the most efficient way to run the necessary software. The introduction of programmable dataplanes opens up the possibility to run software directly in the dataplane with lower latency and higher energy efficiency than general purpose servers. Thus, the concept of in‐network computing is introduced. This paper addresses the challenges associated with executing software resorting to programmable networking devices while presenting a high level conceptu
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Papadopoulos, Konstantinos, Panagiotis Papadimitriou, and Chrysa Papagianni. "Deterministic and Probabilistic P4-Enabled Lightweight In-Band Network Telemetry." January 17, 2024. https://doi.org/10.5281/zenodo.10522553.

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In-band network telemetry (INT), empowered by programmable dataplanes such as P4, comprises a viable ap- proach to network monitoring and telemetry analysis. However, P4-INT as well as other existing frameworks for INT yield a substantial transmission overhead, which grows linearly with the number of hops and the number of telemetry values. To address this issue, we present a deterministic and a probabilistic technique for lightweight INT, termed as DLINT and PLINT, respectively. In particular, DLINT exercises per-flow aggregation by spreading the telemetry values across the packets of a flow.
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Jurkiewicz, Piotr, Bartosz Kądziołka, Mirosław Kantor, Robert Wójcik, and Jerzy Domżał. "Elephant Flow Detection with Random Forest Models under Programmable Network Dataplane Constraints." IEEE Access, 2024, 1. http://dx.doi.org/10.1109/access.2024.3485588.

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Dissertations / Theses on the topic "Programmable Dataplanes"

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Jose, Matthews. "In-network real-value computation on programmable switches." Electronic Thesis or Diss., Université de Lorraine, 2023. http://docnum.univ-lorraine.fr/ulprive/DDOC_T_2023_0057_JOSE.pdf.

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L'arrivée des switchs ASIC programmables de nouvelle génération a obligé la communauté des réseaux à repenser le fonctionnement des réseaux. La possibilité de reconfigurer la logique de traitement des paquets par le plan de transfert de données sans modifier le matériel sous-jacent et l'introduction de primitives de mémoire à état ont suscité un regain d'intérêt pour les cas d'utilisation qui peuvent être déchargés sur le plan de transfert de données. Cependant, les commutateurs programmables ne prennent toujours pas en charge les calculs à valeur réelle et obligent à utiliser des serveurs ext
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Shaker, Maher. "A Dataplane Programmable Traffic Marker using Packet Value Concept." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-85825.

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Real-time sensitive network applications are emerging and require ultra-low latency to reach the desired QoS. A main issue that contributes to latency is excessive buffering at intermediate switches and routers. Existing queuing strategies that aim to reduce buffering induced latency typically apply a single queue AQM that does not support service differentiation and treats all packets equally. The recently proposed per packet value framework utilizes a packet value marker and a packet value aware AQM to solve this issue by supporting service differentiation in a single queue and introducing m
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Conference papers on the topic "Programmable Dataplanes"

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Wei, Cuidi, Shaoyu Tu, Toru Hasegawa, et al. "Envisioning a Unified Programmable Dataplane to Monitor Slow Attacks." In 2024 IEEE 32nd International Conference on Network Protocols (ICNP). IEEE, 2024. https://doi.org/10.1109/icnp61940.2024.10858535.

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Cesen, Fabricio E. Rodriguez, P. Gyanesh Kumar Patra, Christian Esteve Rothenberg, and Gergely Pongracz. "Design, Implementation and Evaluation of IPv4/IPv6 Longest Prefix Match support in P4 Dataplanes." In XVII Workshop em Desempenho de Sistemas Computacionais e de Comunicação. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/wperformance.2018.3319.

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New trends in dataplane programmability inside Software Defined Networking (SDN) paradigm are in an effort to bring multi-platform support with a high-level definition of the dataplane pipeline functions. The MultiArchitecture Compiler System for Abstract Dataplanes (MACSAD) can integrate the Protocol-Independent Packet Processors (P4) domain-specific language and the OpenDataPlane Project (ODP) APIs, to define a programmable dataplane across multiple targets in a unified compiler system. In this paper, we present and evaluate the IPv4/IPv6 Longest Prefix Match (LPM) support in MACSAD. We deve
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Santos, Alexandre, José Quevedo, and Daniel Corujo. "Realizing Zenoh with programmable dataplanes." In ANCS '21: Symposium on Architectures for Networking and Communications Systems. ACM, 2021. http://dx.doi.org/10.1145/3493425.3502761.

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Agape, Andrei-Alexandru, Madalin Claudiu Danceanu, Rene Rydhof Hansen, and Stefan Schmid. "P4Fuzz: Compiler Fuzzer forDependable Programmable Dataplanes." In ICDCN '21: International Conference on Distributed Computing and Networking 2021. ACM, 2020. http://dx.doi.org/10.1145/3427796.3427798.

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Glebke, Rene, Dirk Trossen, Ike Kunze, et al. "Service-based Forwarding via Programmable Dataplanes." In 2021 IEEE 22nd International Conference on High Performance Switching and Routing (HPSR). IEEE, 2021. http://dx.doi.org/10.1109/hpsr52026.2021.9481814.

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Sultana, Nik, Deborah Shands, and Vinod Yegneswaran. "A case for remote attestation in programmable dataplanes." In HotNets '22: The 21st ACM Workshop on Hot Topics in Networks. ACM, 2022. http://dx.doi.org/10.1145/3563766.3564100.

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Hou, Kaiyu, Dhiraj Saharia, Vinod Yegneswaran, and Phillip Porras. "LANTERN: Layered Adaptive Network Telemetry Collection for Programmable Dataplanes." In CoNEXT 2023: The 19th International Conference on emerging Networking EXperiments and Technologies. ACM, 2023. http://dx.doi.org/10.1145/3630047.3630194.

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Bose, Abhik, Diptyaroop Maji, Prateek Agarwal, Nilesh Unhale, Rinku Shah, and Mythili Vutukuru. "Leveraging Programmable Dataplanes for a High Performance 5G User Plane Function." In APNet 2021: 5th Asia-Pacific Workshop on Networking. ACM, 2021. http://dx.doi.org/10.1145/3469393.3469400.

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Pontarelli, Salvatore, Valerio Bruschi, Marco Bonola, and Giuseppe Bianchi. "On offloading programmable SDN controller tasks to the embedded microcontroller of stateful SDN dataplanes." In 2017 IEEE Conference on Network Softwarization (NetSoft). IEEE, 2017. http://dx.doi.org/10.1109/netsoft.2017.8004225.

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Patronas, Giannis, Dimitris Syrivelis, Paraskevas Bakopoulos, et al. "Software-defined, programmable L1 dataplane: demonstration of fabric hardware resilience using optical switches." In Optical Fiber Communication Conference. Optica Publishing Group, 2023. http://dx.doi.org/10.1364/ofc.2023.th2a.15.

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We propose a programmable optical fabric design for Data Center networks that extends SDN to L1. We present experiments on our HPC/ML testbed leveraging the programmable network to automatically failover from hardware or software failures.
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