Modeling Energy Consumption for Task-Offloading Decisions on Mobile and Embedded Devices

Christoph Niemann, Christian Ewert, Henning Puttnies, Michael Rethfeldt, Dirk Timmermann, Peter Danielis


Connected mobile and embedded devices including tablets, smartphones, and smartwatches but also IoT sensors and actuators as well as medical implants are subject to a rapid development in terms of their numbers and computing power. However, these devices have energy limitations, e.g., due to limited energy supplies. In order for networked devices to be able to manage their energy, they can offload tasks to other devices. However, they need to estimate the energy demand to execute the tasks in order to take offloading decisions. This paper proposes energy models for estimating the energy consumption for task processing derived from practical measurements for exemplary tasks. The task-processing energy consumption models are implemented in the OMNeT++ simulator to allow simulative, accurate task-offloading investigations.

Original languageEnglish
Title of host publication2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech)
Publication date03.2020
Publication statusPublished - 03.2020


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