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        <identifier>oai:drops-oai.dagstuhl.de:12006</identifier>
        <datestamp>2024-03-06T10:30:55Z</datestamp>
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          <dc:title>Detection of Fog Network Data Telemetry Using Data Plane Programming</dc:title>
          <dc:creator>Zhou, Zifan</dc:creator>
          <dc:creator>Ollora Zaballa, Eder</dc:creator>
          <dc:creator>Berger, Michael Stübert</dc:creator>
          <dc:creator>Yan, Ying</dc:creator>
          <dc:subject>SDN</dc:subject>
          <dc:subject>P4</dc:subject>
          <dc:subject>P4Runtime</dc:subject>
          <dc:subject>control planes</dc:subject>
          <dc:subject>Fog</dc:subject>
          <dc:subject>Edge</dc:subject>
          <dc:description>Fog computing has been introduced to deliver Cloud-based services to the Internet of Things (IoT) devices. It locates geographically closer to IoT devices than Cloud networks and aims at offering latency-critical computation and storage to end-user applications. To leverage Fog computing for computational offloading from end-users, it is important to optimize resources in the Fog nodes dynamically. Provisioning requires knowledge of the current network state, thus, monitoring mechanisms play a significant role to conduct resource management in the network. To keep track of the state of devices, we use P4, a data-plane programming language, to describe data-plane abstraction of Fog network devices and collect telemetry without the intervention of the control plane or adding a big amount of overhead. In this paper, we propose a software-defined architecture with a programmable data plane for data telemetry detection that can be integrated into Fog network resource management. After the implementation of detecting data telemetry based on In-Band Network Telemetry (INT) within a Mininet simulation, we show the available features and preliminary Fog resource management based on the collected data telemetry and future telemetry-based traffic engineering possibilities.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Zifan Zhou and Eder Ollora Zaballa and Michael Stübert Berger and Ying Yan</dc:contributor>
          <dc:date>2020</dc:date>
          <dc:relation>Is Part Of OASIcs, Volume 80, 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:identifier>doi:10.4230/OASIcs.Fog-IoT.2020.12</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-120062</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.12</dc:identifier>
          <dc:language>eng</dc:language>
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