Capturing, Storing, Analyzing and Sharing Energy Consumption Data
We have been exploring the applicability of domain modeling techniques to manage the complexity of an integrated architecture for a software-intensive system-of-systems such as the GreenLight instrument. Modeling plays an important role in all requirements engineering activities, serving as a common interface to domain analysis, requirements elicitation, specification, assessment, documentation, and evolution. Models can help in defining the questions for stakeholders and surfacing hidden requirements. Ultimately, the requirements have to be mapped to the precise specification of the system and the mapping should be kept up to date during the evolution of requirements or the architecture.
In Year 1, our first efforts focused on identifying the set of stakeholders for the Instrument and capturing a preliminary set of requirements regarding data management, which were crucial in Year 2 for identifying green experiments that would help us relate energy consumption with the utilization of the various resources made available by the GreenLight instrument. By means of a sequence of working meetings with other PIs and their team members, we identified two classes of system-related data producers: the communication infrastructure and the underlying physical computing infrastructure; and several classes of environment data producers (e.g., cooling fans, cold water intake, temperature sensors, etc.). On the other hand, there are more classes of data consumers with requirements as diverse as reading CPU temperature at 10ms intervals, to optimizing cooling fans air flow at minute granularity, to measuring PDU phases per rack and building live depictions of the power load of the Instrument.
As part of an ongoing iterative process, in Year 2 the data collection and management requirements were checked for errors such as incompleteness, contradictions, ambiguities, inadequacies in respect to the real needs - which all can have negative effects on the system development costs and the quality of the resulting product.
Technical White PapersEnergy Consumption Data 2010