Design of a Sliding Window over Asynchronous Event Streams

TL;DR

This paper introduces a novel approach to maintain sliding windows over asynchronous event streams by modeling snapshots as a convex distributive lattice, enabling effective predicate detection in distributed, asynchronous environments.

Contribution

It presents a new lattice-based model (Lat-Win) for asynchronous event streams and an algorithm to maintain it at runtime, addressing challenges in distributed sliding window processing.

Findings

Lat-Win effectively models asynchronous event stream snapshots.

The maintenance algorithm performs well in dynamic, distributed environments.

Sliding windows are necessary for effective event stream processing in asynchronous settings.

Abstract

The proliferation of sensing and monitoring applications motivates adoption of the event stream model of computation. Though sliding windows are widely used to facilitate effective event stream processing, it is greatly challenged when the event sources are distributed and asynchronous. To address this challenge, we first show that the snapshots of the asynchronous event streams within the sliding window form a convex distributive lattice (denoted by Lat-Win). Then we propose an algorithm to maintain Lat-Win at runtime. The Lat-Win maintenance algorithm is implemented and evaluated on the open-source context-aware middleware we developed. The evaluation results first show the necessity of adopting sliding windows over asynchronous event streams. Then they show the performance of detecting specified predicates within Lat-Win, even when faced with dynamic changes in the computing environment.