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DTSTAMP:20211207T055409Z
LOCATION:240-241-242
DTSTART;TZID=America/Chicago:20211119T094000
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UID:submissions.supercomputing.org_SC21_sess337_ws_urgent104@linklings.com
SUMMARY:Evaluating Policy-Driven Adaptation on the Edge-to-Cloud Continuum
DESCRIPTION:Workshop\n\nEvaluating Policy-Driven Adaptation on the Edge-to
 -Cloud Continuum\n\nBalouek-Thomert, Rodero, Parashar\n\nDeveloping data-d
 riven applications requires orchestrating data-to-discovery pipelines acro
 ss distributed data sources and computing units. Realizing such pipelines 
 poses two major challenges: programming analytics that reacts at runtime t
 o unforeseen events, and adaptation of the resources and computing paths b
 etween the edge and the cloud. While these concerns are interdependent, th
 ey must be separated during the design process of the application and the 
 deployment operations of the infrastructure.\n\nThis work proposes a syste
 m stack for the adaptation of distributed analytics across the computing c
 ontinuum.  We evaluate the ability to continually balance the computation 
 or data movement’s cost with the value of operations to the application ob
 jectives.  Using a disaster response application, we observe that the syst
 em can select appropriate configurations while managing trade-offs.  The e
 valuation shows that our model is able to adapt to variations in the data 
 input size, bandwidth, and CPU capacities with minimal deadline violations
  (less than 10%).\n\nTag: Applications, Big Data, Computational Science, D
 ata Analytics, Emerging Technologies, Extreme Scale Computing, Machine Lea
 rning and Artificial Intelligence\n\nRegistration Category: Workshop Reg P
 ass
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