Carat: Collaborative Energy Debugging

Authors:

Adam J. Oliner, AMP Lab, University of California, Berkeley

Abstract:

We aim to detect and diagnose code misbehavior that wastes energy, which we call energy bugs. I will describe a method and implementation, called Carat, for performing such diagnosis on mobile devices. Carat takes a collaborative, black-box approach. A non-invasive client app sends intermittent, coarse-grained measurements to a server, which identifies correlations between higher expected energy use and client properties like the running apps, the device model, and the operating system. Carat has been deployed on more than a quarter of a million devices and has detected thousands of app instances exhibiting energy bugs in the wild.

Adam J. Oliner, University of California, Berkeley

Adam J. Oliner is a postdoc in the EECS Department at UC Berkeley, working in the AMP Lab. Before starting at Berkeley, he earned a Ph.D. in computer science from Stanford University, where he was a DOE High Performance Computer Science Fellow and Honorary Stanford Graduate Fellow. Adam received a MEng in EECS from MIT, where he also earned undergraduate degrees in computer science and mathematics. His research focuses on understanding complex systems, most recently applied to diagnosing energy bugs in mobile devices.

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