Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems

To sustain perpetual operation, systems that harvest environmental energy must carefully regulate their usage to satisfy their demand. Regulating energy usage is challenging if a system's demands are not elastic and its hardware components are not energy-proportional, since it cannot precisely scale its usage to match its supply. Instead, the system must choose when to satisfy its demands based on its current energy reserves and predictions of its future energy supply. In this paper, we explore the use of weather forecasts to improve a system's ability to satisfy demand by improving its predictions. We analyze weather forecast, observational, and energy harvesting data to formulate a model that translates a weather forecast to a solar or wind energy harvesting prediction, and quantify its accuracy. We evaluate our model for both energy sources in the context of two different energy harvesting sensor systems with inelastic demands: a testbed that leases sensors to external use...

• Type: Journal
• Year: 2010
• Where: SECON
• Authors: Navin Sharma, Jeremy Gummeson, David Irwin, Prashant J. Shenoy
• Keywords: Communications, Predictions, SECON 2010, Sensor Systems, Weather Forecasts