Combining it all: Cost minimal and low-latency stream processing across distributed heterogeneous infrastructures

Abstract

Control mechanisms of stream processing applications (SPAs) that ensure latency bounds at minimal runtime cost mostly target a specific infrastructure, e.g., homogeneous nodes. With the growing popularity of the Internet of Things, fog, and edge computing, SPAs are more often distributed on heterogeneous infrastructures, triggering the need for a holistic SPA-control that still considers heterogeneity. We therefore combine individual control mechanisms via the latency-distribution problem that seeks to distribute latency budgets to individually managed components of distributed SPAs for a lightweight yet effective end-to-end control. To this end, we introduce a hierarchical control architecture, give a formal definition of the latency-distribution problem, and provide both an ILP formulation to find an optimal solution as well as a heuristic approach, thereby enabling the combination of individual control mechanisms into one SPA while ensuring global cost minimality. Our evaluations show that both solutions are effective---while the heuristic approach is only slightly more costly than the optimal ILP solution, it significantly reduces runtime and communication overhead.