2003 · 483 citations · 11 references
ComputingComputer ScienceComputer SystemsCluster ComputingDistributed SystemsParallel ComputingDistributed ComputingDistributed Data ProcessingDistributed Database ArchitectureDistributed Systems ArchitectureDistributed Systems DesignStream ProcessingDistributed ScalabilityDistributed Stream ProcessingFederated ManagementLarge-scale Data ProcessingLoad DistributionStream Processing Scalability
Stream processing fits a large class of new applications for which conventional DBMSs fall short. Because many stream-oriented systems are inherently geographically distributed and because distribution offers scalable load management and higher availability, future stream processing systems will operate in a distributed fashion. They will run across the Internet on computers typically owned by multiple cooperating administrative domains. This paper describes the architectural challenges facing the design of large-scale distributed stream processing systems, and discusses novel approaches for addressing load management, high availability, and federated operation issues. We describe two stream processing systems, Aurora * and Medusa, which are being designed to explore complementary solutions to these challenges. 1
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Aurora: a new model and architecture for data stream management
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