FG Verteilte Systeme und Betriebssysteme
Embedded systems, e.g. nodes within sensor networks, often have tight bound goals for lifetime while running from a not renewable energy source. Mostly batteries are used, which are vulnerable to temperature and non-linear effects. Additionally, variations within the hardware or induced by the software make the prediction of the available and consumed energy a complicated task. To reach certain lifetime goals under these influences, online energy management is necessary. For a fine-grained management on the level of individual sub-tasks, it is necessary to know where in the system the energy is consumed.
In this work, we extend our online energy accounting approach to enable online energy management. We present ways to control application and device behavior, and, thus, energy using energy budgets. First experiments yield promising results, reaching their lifetime goals while maintaining a high application quality.
Nodes within sensor networks often have tight bound goals for the lifetime while running from a non-renewable energy source. Variations within the hardware or induced by the software complicate the prediction of the energy consumption. Additionally, batteries are vulnerable to temperature and non-linear effects. To reach certain lifetime goals under these influences without sacrificing energy due to pessimistic estimations, online energy management is necessary. At Sensorcomm 2015 we presented policies to control the behavior of applications and devices using energy budgets. This paper is an extended version which adds further details and the evaluation of the proposed dynamic energy management in a real-world scenario.
Nodes within sensor networks often have tight bound goals for the lifetime while running from a non-renewable energy source. Variations within the hardware or induced by the software complicate the prediction of the energy consumption. Additionally, batteries are vulnerable to temperature and non-linear effects. To reach certain lifetime goals under these influences without sacrificing energy due to pessimistic estimations, online energy management is necessary. In this paper, we present policies to control the behavior of applications and devices using energy budgets. First experiments yield promising results, with nodes reaching their lifetime goals while maintaining a high application quality.
Implicit Sleep Mode Determination in Power Management of Event-driven Deeply Embedded Systems
(2008)
Currently, new storage technologies which unite the latency and byte-addressability of DRAM with the persistence of disks are being developed. This non-volatile memory (NVRAM) may start a software revolution. Traditionally, software was developed for two levels of storage and NVRAM reduces the hierarchy to a single-level store. Current research projects are already exploring the potential of NVRAM, but they face a challenge when they want to evaluate the performance: The new hardware is not yet available.
In this paper, we discuss why benchmark results which are gained on existing DRAM are insufficient for a prediction of the performance on NVRAM. Either existing instructions have to be changed or new ones have to be introduced. We further show that the bochs emulator can be used to build systems which resemble NVRAM, to predict the NVRAM's consequences, and it even allows a comparison of algorithms for NVRAM.