Chemistry-Inspired Adaptive Stream Processing

Abstract

Abstract. Stream processing engines have appeared as the next generation of data processing systems, facing the needs for low-delay processing. While these systems have been widely studied recently, their ability to adapt their processing logics at run time upon the detection of some events calling for adaptation is still an open issue. Chemistry-inspired models of computation have been shown to ease the specification of adaptive systems. In this paper, we argue that a higherorder chemical model can be used to specify such an adaptive SPE in a natural way. We also show how such programming abstractions can get enacted in a decentralised environment.