Combining human and machine computing elements for analysis via crowdsourcing

Julian Jarrett, Iman Saleh, M. Brian Blake, Rohan Malcolm, Sean Thorpe, Tyrone Grandison

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Crowd computing leverages human input in order to execute tasks that are computationally expensive, due to complexity and/or scale. Combined with automation, crowd computing can help solve problems efficiently and effectively. In this work, we introduce an elasticity framework that adaptively optimizes the use of human and automated software resources in order to maximize overall performance. This framework includes a quantitative model that supports elasticity when performing complex tasks. Our model defines a task complexity index and an elasticity index that is used to aid in decision support for assigning tasks to respective computing elements. Experiments demonstrate that the framework can effectively optimize the use of human and machine computing elements simultaneously. Also, as a consequence, overall performance is significantly enhanced.

Original languageEnglish
Title of host publicationCollaborateCom 2014 - Proceedings of the 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages312-321
Number of pages10
ISBN (Print)9781631900433
DOIs
StatePublished - Jan 19 2015
Externally publishedYes
Event10th IEEE/EAI International Conference on Collaborative Computing, CollaborateCom 2014 - Miami, United States
Duration: Oct 22 2014Oct 25 2014

Other

Other10th IEEE/EAI International Conference on Collaborative Computing, CollaborateCom 2014
CountryUnited States
CityMiami
Period10/22/1410/25/14

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Keywords

  • crowdsouring
  • elastic systems
  • experimentation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Software

Cite this

Jarrett, J., Saleh, I., Blake, M. B., Malcolm, R., Thorpe, S., & Grandison, T. (2015). Combining human and machine computing elements for analysis via crowdsourcing. In CollaborateCom 2014 - Proceedings of the 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing (pp. 312-321). [7014577] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.4108/icst.collaboratecom.2014.257298