Fine-grained power modeling for smartphones using system call tracing

By Abhinav Pathak, Y. C. Hu, Ming Zhang, Paramvir Victor Bahl, Yi-Min Wang. European Conference on Computer Systems, 2011

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Empowering developers to estimate app energy consumption (2012, background): “To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior speci.c permission and/or a fee.”
Where is the energy spent inside my app?: fine grained energy accounting on smartphones with Eprof (2012, methodology): “For a productive power state, linear regression is used to correlate the duration the component stays in that state with the parameters (workload) of the system call that drove the FSM to the state, and energy consumption at that state is deduced [4].”
Estimating mobile application energy consumption using program analysis (2013, background): “A complementary approach [16], [17] explicitly models the state transitions between hardware power states of smartphone hardware components (CPU, WiFi, GPS etc.”
Quantifying the energy cost of data movement for emerging smart phone workloads on mobile platforms (2014, methodology): “[17] developed a power model based on system call tracing and demonstrated that energy estimation is possible using their developed power model.”