Opportunistic spatio-temporal event processing for mobile situation awareness

  • Authors:

  • Kirak Hong;David Lillethun;Umakishore Ramachandran;Beate Ottenwälder;Boris Koldehofe

  • Affiliations:

  • Georgia Institute of Technology, Atlanta, GA, USA;Georgia Institute of Technology, Atlanta, GA, USA;Georgia Institute of Technology, Atlanta, GA, USA;University of Stuttgart, Stuttgart, Germany;University of Stuttgart, Stuttgart, Germany

  • Venue:
  • Proceedings of the 7th ACM international conference on Distributed event-based systems
  • Year:
  • 2013

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Abstract

With the proliferation of mobile devices and sensors, mobile situation awareness is becoming an important class of applications. The key requirement of this class of applications is low-latency processing of events stemming from sensor data in order to provide timely situational information to mobile users. To satisfy the latency requirement, we propose an opportunistic spatio-temporal event processing system that uses prediction-based continuous query handling. Our system predicts future query regions for moving consumers and starts processing events early so that the live situational information is available when the consumer reaches the future location. In contrast to existing systems, our system provides timely information about a consumer's current position by hiding computation latency for processing recent events. To evaluate our system, we measure the quality of results and timeliness of live situational information with various query parameters. Our evaluation shows that we can achieve highly meaningful query results with near-zero latency in most cases.