Low-latency stream processing applications (SPA) distribute the event streams on parallel instances of the application’s operators to avoid queuing. Each operator has a set of processing nodes for its instances. Edge and fog infrastructures promise, among other things, low communication latency and are thus of interest for low-latency SPAs. Yet, they include heterogeneous, even volatile nodes which makes the parallel processing of SPAs challengingAvailable solutions for parallel SPAs often assume homogeneity and stable infrastructures.Thus, we aim to balance the stream processing among heterogeneous, instable infrastructures using a decentralized control mechanism. We propose a decentralized, dynamic, and lightweight approach to re-balance SPA-load according to the nodes current performance, while minimizing latencies. In doing so, we introduce the Coda-EFC framework for window-based stream processing on heterogeneous distributed infrastructures. It dynamically adapts its load balancing to node performance without computing quickly outdated schedules and aims for latency-optimal load balancing. We introduce two adaptive load balancing strategiesone tailored for heterogeneous, dynamic infrastructures, the other an adaptation of a state-of-the art approach.