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DTSTAMP:20260422T000713Z
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DTSTART;TZID=America/Denver:20231113T093700
DTEND;TZID=America/Denver:20231113T095500
UID:submissions.supercomputing.org_SC23_sess450_ws_worksp117@linklings.com
SUMMARY:A Data Science Pipeline Synchronization Method for Edge-Fog-Cloud 
 Continuum
DESCRIPTION:Dante D. Sanchez-Gallegos (University Carlos III of Madrid, Sp
 ain); J. L. Gonzalez-Compean (Cinvestav Tamaulipas); Jesus Carretero (Univ
 ersity Carlos III of Madrid, Spain); and Heidy Marin-Castro (Cátedras CONA
 CYT - Universidad Autónoma de Tamaulipas)\n\nThis paper presents an adapti
 ve continuum synchronization method for data science pipelines deployed on
  edge-fog-cloud infrastructures. In a diagnostic phase, a model, based on 
 the Bernoulli principle, is used as an analogy to create a global represen
 tation of bottlenecks in a pipeline. In a supervision phase, a watchman/se
 ntinel cooperative system monitors and captures the throughput of the pipe
 line stages to create a bottleneck-stage scheme. In a rectification phase,
  this system produces replicas of stages identified as bottlenecks to miti
 gate the workload congestion using implicit parallelism and load balancing
  algorithms. This method is automatically and transparently invoked to pro
 duce in runtime a steady continuum dataflow. To test our proposal, we cond
 ucted a case study about the processing of medical and satellite data on f
 og-cloud infrastructures. The evaluation revealed that this method creates
 , without characterizing workloads nor knowing infrastructure details, con
 tinuum dataflows, which yield a competitive performance with solutions in 
 the state-of-the-art.\n\nTag: Data Analysis, Visualization, and Storage, L
 arge Scale Systems, Programming Frameworks and System Software, Reproducib
 ility, Resource Management, Runtime Systems\n\nRegistration Category: Work
 shop Reg Pass\n\nSession Chairs: Silvina Caino-Lores (National Institute f
 or Research in Digital Science and Technology (Inria)) and Anirban Mandal 
 (Renaissance Computing Institute (RENCI), University of North Carolina at 
 Chapel Hill)\n\n
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