Now showing items 1-6 of 6

    • CAPSULE: Language and system support for efficient state sharing in distributed stream processing systems 

      Losa, G.; Kumar, V.; Andrade, H.; Gedik, Buğra; Hirzel, M.; Soulé, R.; Wu, K. -L. (ACM, 2012)
      Data stream processing applications are often expressed as data flow graphs, composed of operators connected via streams. This structured representation provides a simple yet powerful paradigm for building large-scale, ...
    • Diversity and novelty in web search, recommender systems and data streams 

      Santos, R. L. T.; Castells, P.; Altingovde, I. S.; Can, Fazlı (Association for Computing Machinery, 2014-02)
      This tutorial aims to provide a unifying account of current research on diversity and novelty in the domains of web search, recommender systems, and data stream processing.
    • Elastic scaling for data stream processing 

      Gedik, B.; Schneider S.; Hirzel M.; Wu, Kun-Lung (IEEE Computer Society, 2014)
      This article addresses the profitability problem associated with auto-parallelization of general-purpose distributed data stream processing applications. Auto-parallelization involves locating regions in the application's ...
    • Generic windowing support for extensible stream processing systems 

      Gedik, B. (John Wiley & Sons Ltd., 2014)
      Stream processing applications process high volume, continuous feeds from live data sources, employ data-in-motion analytics to analyze these feeds, and produce near real-time insights with low latency. One of the fundamental ...
    • Pipelined fission for stream programs with dynamic selectivity and partitioned state 

      Gedik, B.; Özsema, H. G.; Öztürk, Ö. (Academic Press, 2016)
      There is an ever increasing rate of digital information available in the form of online data streams. In many application domains, high throughput processing of such data is a critical requirement for keeping up with the ...
    • Sliding windows over uncertain data streams 

      Dallachiesa, M.; Jacques-Silva, G.; Gedik, B.; Wu, Kun-Lung; Palpanas, T. (Springer U K, 2015)
      Uncertain data streams can have tuples with both value and existential uncertainty. A tuple has value uncertainty when it can assume multiple possible values. A tuple is existentially uncertain when the sum of the ...