Geostreaming in cloud

  • Authors:

  • Seyed Jalal Kazemitabar;Farnoush Banaei-Kashani;Dennis McLeod

  • Affiliations:

  • University of Southern California, Los Angeles, CA;University of Southern California, Los Angeles, CA;University of Southern California, Los Angeles, CA

  • Venue:
  • Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoStreaming
  • Year:
  • 2011

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Abstract

In recent years, geospatial databases have been commercialized and widely exposed to mass users. Current exponential growth in data generation and querying rates for these data highlights the importance of efficient techniques for streaming. Traditional database technology, which operates on persistent and less dynamic data objects does not meet the requirements for efficient geospatial data streaming. Geostreaming, the intersection of data stream processing and geospatial querying, is an ongoing research focus in this area. In this paper, we describe why cloud is the most appropriate infrastructure in which to support geospatial stream data processing. First, we argue that cloud best fits the requirements of a large-scale geostreaming application. Second, we propose ElaStream, a general cloud-based streaming infrastructure that enables huge parallelism by means of the divide, conquer, and combine paradigm. Third, we examine key related work in the data streaming and (geo)spatial database fields, and describe the challenges ahead to build scalable cloud-based geostreaming applications.