Resa: Realtime elastic streaming analytics in the cloud

Tian Tan, Yin Yang, Richard T.B. Ma, Yong Yu, Marianne Winslett, Zhenjie Zhang

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

5 Citations (Scopus)

Abstract

We propose Resa, a novel framework for robust, elastic and realtime stream processing in the cloud. In addition to traditional functionalities of streaming and cloud systems, Resa provides (i) a novel mechanism that handles dynamic additions and removals nodes in an operator, and (ii) a node re-assignment scheme that minimizes output latency using a queuing model. We have implemented Resa on top of Twitter Storm. Experiments using real data demonstrate the effectiveness and efficiency of Resa.

Original languageEnglish
Title of host publicationSIGMOD 2013 - International Conference on Management of Data
Number of pages1
DOIs
Publication statusPublished - 29 Jul 2013
Event2013 ACM SIGMOD Conference on Management of Data, SIGMOD 2013 - New York, NY, United States
Duration: 22 Jun 201327 Jun 2013

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Other

Other2013 ACM SIGMOD Conference on Management of Data, SIGMOD 2013
CountryUnited States
CityNew York, NY
Period22/6/1327/6/13

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Keywords

  • Cloud
  • Migration
  • Resource allocation
  • Stream

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Tan, T., Yang, Y., Ma, R. T. B., Yu, Y., Winslett, M., & Zhang, Z. (2013). Resa: Realtime elastic streaming analytics in the cloud. In SIGMOD 2013 - International Conference on Management of Data (Proceedings of the ACM SIGMOD International Conference on Management of Data). https://doi.org/10.1145/2463676.2465343