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Demo: Scaling on the Edge – A Benchmarking Suite for Human-in-the-Loop Applications
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. (James Gross, Edge Computing)ORCID iD: 0000-0002-3383-2335
Carnegie Mellon University. (Elijah Group at CMU)ORCID iD: 0000-0001-9484-8501
Carnegie Mellon University. (Elijah Group at CMU)ORCID iD: 0000-0002-2187-2049
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Information Science and Engineering.ORCID iD: 0000-0001-6682-6559
2018 (English)In: 2018 IEEE/ACM Symposium on Edge Computing (SEC), IEEE , 2018Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Benchmarking human-in-the-loop appli-cations running on edge computing in-frastructure is complex given their nature,which heavily depends on the actions takenby the human user. This limits reproducibil-ity as well as feasibility of performance eval-uations. We propose a methodology andpresent a benchmarking suite that can ad-dress these challenges. Our core idea restson recording traces of these applicationswhich are played out in a controlled fashionbased on an underlying model of human be-havior. The traces are exposed to the origi-nal backend compute process of the respec-tive human-in-the-loop application, gener-ating realistic feedback. This allows for anautomated system which greatly simplifiesbenchmarking large scale scenarios.

Place, publisher, year, edition, pages
IEEE , 2018.
Keywords [en]
Human-in-the-Loop, Edge Computing, Cognitive Assistance, Performance Evaluation, Scaling of Distributed Systems
National Category
Communication Systems Computer Systems
Research subject
Computer Science; Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-241113DOI: 10.1109/sec.2018.00031OAI: oai:DiVA.org:kth-241113DiVA, id: diva2:1277880
Conference
2018 IEEE/ACM Symposium on Edge Computing (SEC)
Available from: 2019-01-11 Created: 2019-01-11 Last updated: 2019-01-11Bibliographically approved

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Publisher's full texthttps://doi.org/10.1109%2Fsec.2018.00031

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Gross, James

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