A Workflow-Inspired, Modular and Robust Approach to Experiments in Distributed Systems

Experimentation in large-scale distributed systems research is very challenging due to the size and complexity of modern systems and applications spanning domains of high performance computing, P2P networks, cloud computing, etc. Some obstacles that each researcher must face are: the difficulty of properly structuring experiments due to their complexity, the inflexibility of existing methodologies and tools and the scalability problems resulting from the size of studied systems. In this paper, we propose a novel method of representing and executing experiments that solves these problems. To this end, we present an interdisciplinary approach to the control of large-scale experiments in distributed systems research that draws its foundations from workflow management and scientific workflows. This workflow-inspired approach distinguishes itself by its representation of experiments, modular architecture and robust error handling. We show how the aforementioned problems are solved by our approach in an exemplary performance study of an HTTP server.