Pipeline Modeling via DAG

As mentioned in Network Typology section, ChimeraPy uses a peer-to-peer network to represent its data pipeline. To be more precise, ChimeraPy uses a directed acyclic graph (DAG) to model the data pipeline and data streams. The implications of a DAG is that the data streams need to be directed, meaning it must have a source and destination. Acyclic implies that the graph does not permit a cycle. This is because a cycle in a data pipeline would result in a disaster! That is because each Node will only execute once it has at least collected 1 sample from each of its dependencies, therefore a cycle to cause a deadlock.

From our use of ChimeraPy, a DAG can commonly be broken into 3 layers: data sources, data processing, and data feedback. Moreover, the DAG provides us with an explicit representation of the execution schedule, therefore no need of a scheduler.