@misc{SieberNolte, author = {Sieber, Andr{\´e} and Nolte, J{\"o}rg}, title = {Online device-level energy accounting for wireless sensor nodes}, series = {Wireless Sensor Networks, Proceedings of the 10th European conference on Wireless Sensor Networks, Ghent, Belgien, 2013}, journal = {Wireless Sensor Networks, Proceedings of the 10th European conference on Wireless Sensor Networks, Ghent, Belgien, 2013}, publisher = {Springer}, address = {Berlin [u.a]}, isbn = {978-3-642-36672-7}, pages = {149 -- 164}, abstract = {Energy is the crucial factor for the lifetime of wireless sensor networks. Nonlinear battery effects and nonuniform workload distribution can lead to early node failures. This makes it necessary to manage energy consumption. But to manage energy it is essential to know how much energy is spent by the system. Additionally, for a more fine-grained management it is necessary, to know where the energy is spent. This can be a complicated task, since nodes are not identical due to device variations and the consumption can change over time. In this paper we present an online energy accounting approach which focuses on simplicity instead on fine granularity and timing accuracy. We argue that the efficacy of an energy accounting model depends more on the input consumption data than on exact timing, especially when the real consumption varies between nodes and in time. Results show that this approach is capable of correctly accounting the energy that nodes spend in scenarios with deviating environment conditions.}, language = {en} } @inproceedings{SieberKarnapkeNolte, author = {Sieber, Andr{\´e} and Karnapke, Reinhardt and Nolte, J{\"o}rg}, title = {From Energy Accounting to Energy Management}, series = {13. GI/ITG Fachgespr{\"a}ch Sensornetze, 25. und 26. September 2014 an der Universit{\"a}t Potsdam}, booktitle = {13. GI/ITG Fachgespr{\"a}ch Sensornetze, 25. und 26. September 2014 an der Universit{\"a}t Potsdam}, publisher = {Universit{\"a}t}, address = {Potsdam}, pages = {25 -- 28}, abstract = {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.}, language = {en} }