Supporting Multi-criteria Decision Support Queries over Time-Interval Data Streams

Abstract

Multi-criteria result extraction is crucial in many real-time stream processing applications, such as habitat and disaster monitoring. The ease in expressing user preferences makes skyline queries a popular class of queries. Skyline evaluation is computationally intensive especially over continuous time-interval streams where each object has its own individual expiration time. In this work, we propose TI-Sky – a continuous skyline evaluation framework. TI-Sky strikes a perfect balance between the costs of continuously maintaining the result space upon the arrival of new objects or the expiration of old objects, and the costs of computing the final skyline result from this space whenever a pull-based user query is received. This is achieved by incrementally maintaining a precomputed skyline result space at a higher level of abstraction and digging into the more expensive object-level processing only upon demand. Our experimental study demonstrates the superiority of TI-Sky over existing techniques.