Literature DB >> 34372438

Achieving Low Latency Communications in Smart Industrial Networks with Programmable Data Planes.

Asier Atutxa1, David Franco1, Jorge Sasiain1, Jasone Astorga1, Eduardo Jacob1.   

Abstract

Industrial networks are introducing Internet of Things (IoT) technologies in their manufacturing processes in order to enhance existing methods and obtain smarter, greener and more effective processes. Global predictions forecast a massive widespread of IoT technology in industrial sectors in the near future. However, these innovations face several challenges, such as achieving short response times in case of time-critical applications. Concepts like in-network computing or edge computing can provide adequate communication quality for these industrial environments, and data plane programming has been proved as a useful mechanism for their implementation. Specifically, P4 language is used for the definition of the behavior of programmable switches and network elements. This paper presents a solution for industrial IoT (IIoT) network communications to reduce response times using in-network computing through data plane programming and P4. Our solution processes Message Queuing Telemetry Transport (MQTT) packets sent by a sensor in the data plane and generates an alarm in case of exceeding a threshold in the measured value. The implementation has been tested in an experimental facility, using a Netronome SmartNIC as a P4 programmable network device. Response times are reduced by 74% while processing, and delay introduced by the P4 network processing is insignificant.

Entities:  

Keywords:  IoT; P4; data plane programming; industrial communications; time-critical

Year:  2021        PMID: 34372438     DOI: 10.3390/s21155199

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  A Universal Testbed for IoT Wireless Technologies: Abstracting Latency, Error Rate and Stability from the IoT Protocol and Hardware Platform.

Authors:  Edgar Saavedra; Laura Mascaraque; Gonzalo Calderon; Guillermo Del Campo; Asuncion Santamaria
Journal:  Sensors (Basel)       Date:  2022-05-30       Impact factor: 3.847

  1 in total

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