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Today���s deeply embedded systems, with real-time interactions to the environment, are largely battery-operated, and peripheral modules like LTE, WiFi, and GPS are among the most energy-hungry components of them. These components are often under the direct control of an embedded software. Some pieces of the software program are called energy hotspots if they can be transformed towards better system energy consumption while leaving it logically- and temporally-correct. This paper focuses on three such energy hotspots from the peripheral module perspective. The root causes of the hotspots in the software program are misplaced driver calls: Early acquiring or late releasing of the module causes it to waste energy in the active state, having unnecessary distance between the use operations causes extra tail energy overhead, and unaccounted releasing and re-acquiring of the module causes more energy consumption in comparison to leaving the module unreleased. We provide static analysis methods for the detection and elimination of such energy hotspots automatically with regard to some relations between temporal requirements of the real-time embedded software, the time and energy specifications of the module, and the extreme (worst-case/best-case) execution times of specific pieces of the software program. Our simulation results show about 4.7 to 20 percent of energy reductions after elimination of the energy hotspots of the test programs using our proposed method.

These figures (a) and (b) represent phase portrait and potential energy function of the dynamical system corresponding to the mZK equation for ion-acoustic waves in a magnetized electron-ion plasma with generalized (r, q) distributed electrons for q = 5 and r = 0.1. These figures contain three fixed points P0, P1 and P2 with one separatrix. The figure (a) contains one family of supernonlinear periodic orbits, two families of periodic orbits and one pair of homoclinic orbits at P0. The figure (b) contains the potential energy function with two local minima and one maxima which is necessary condition for supernonlinear wave.