An Efficient Algorithm for Continuous Complex Event Matching Using Bit-Parallelism

Complex event matching has gained a lot of at-tention for evaluating complex queries over event streams. The events composing a complex event occur within a user-specified time window and can be nonconsecutive on the stream. Existing methods widely utilize the state automaton to match complex events. However, the state automaton is typically used for matching consecutive items satisfying a pattern, e.g., the regular expression. To support nonconsecutive event matching, it has to maintain a large number of partial matches and skip irrelevant events, which results in a huge overhead. To avoid this problem, we employ the bit parallelism technique to match complex events continuously in this paper. We utilize a set of bit sequences to represent the events, where each bit is associated with a time slice, and an event is mapped to a 1-bit of the sequence if its timestamp belongs to the time slice. Then, bit-parallel operations are designed to process the constraints defined on the complex event, e.g., the time window limitation, and sequential order of the events, etc. We further propose the bit-parallel algorithms to support continuous complex event matching using these bit operations. Our experiments on real and synthetic datasets demonstrate that our method outperforms the existing methods by up to an order of magnitude in Query efficiency.