Earliest Deadline Scheduling for Continuous Queries over Data Streams

Many stream-based applications have real-time performance requirements for continuous queries over time varying data streams. In order to address this challenge, a real-time continuous query model is presented to process multiple queries with timing constraints. In this model, the execution of one tuple passing through an operator path is modeled as a real-time task instance. A fine-grained scheduling strategy named OP-EDF is proposed for real-time scheduling, which schedules the operator path with the earliest deadline of the waiting tuples at any time slot. The performance of the OP-EDF is analyzed from three aspects: schedulability, response time and system overhead. Furthermore, two improved batch scheduling algorithms, termed OP-EDF-Batch and OP-EDF-Gate, are introduced to decrease system overhead of the OP-EDF. The experiment results show that the proposed continuous query model and improved scheduling algorithms are effective in real-time query processing for data streams with bursty arrival rates.