INFuse: Towards Efficient Context Consistency by Incremental-Concurrent Check Fusion

Nowadays applications are getting increasingly attractive by being capable of adapting their behaviors based on their understanding to running environments (a.k.a. contexts). However, such capability can be subject to illness or even unexpected crash, when contexts, for suffering environmental noises, become inaccurate or even conflict with each other. Fortunately, various constraint checking techniques have been proposed to validate contexts against consistency constraints, in order to guard context consistency for applications in a timely manner. However, with the growth of environmental dynamics and context volume, it is getting more and more challenging to check context consistency in time. In this paper, we propose a novel approach, INFuse, to soundly fuse together two lines of techniques, namely, incremental checking and concurrent checking, for efficient constraint checking. Realizing such check fusion has to address the challenges rising from the gap between the micro analysis for reusable elements in incremental checking and the macro collection of parallel tasks in concurrent checking. INFuse solves the challenges by automatically deciding maximal concurrent boundaries for context changes under checking (i.e., what-correctness problem), and soundly fusing incremental and concurrent checking for context consistency (i.e., how-correctness problem), with theoretical guarantees. Our experimental evaluation with real-world data shows that INFuse could improve constraint checking efficiency by 18.6x–171.1x, as compared with existing state-of-the-art techniques.