D2WORM: A Management Infrastructure for Distributed Data-centric Workflows

Abstract

Unlike traditional activity-flow-based models, data-centric workflows primarily focus on the data to drive a business. This enables the unification of operational management, concurrent process analytics, compliance with process or associated data constraints, and adaptability to changing environments. In this demonstration, we present D2Worm, a Distributed Data-centric Workflow Management system. D2Worm allows users to (1) graphically model data-centric workflows in a declarative fashion based on the Guard-Stage-Milestone (GSM) meta-model, (2) automatically compile the modelled workflow into several fine-granular workflow units (WFUs), and (3) deploy these WFUs on distributed infrastructures. A WFU is a system component that manages a subset of the workflow’s data model and, at the same time, represents part of the global control flow by evaluating conditions over the data. WFUs communicate with each other over a publish/subscribe messaging infrastructure that allows the architecture to scale from a single node to dozens of machines distributed over different data-centers. In addition, D2Worm is able to (4) concurrently execute multiple workflow instances and monitor their behavior in real-time.