The Internet-of-Things (IoT) currently rules many activities in research and development of mobile and wearable devices. This not only refers to smart phones. According to the analysts IDC, the number of sold smart watches tripled from 7.1 million devices in Q3/2014 to 21.2 million devices in Q3/2014 (Farooqui, 2015). In a 2014 analysis, the ABI Research data estimated the market increase for all wearables from 53.8 million devices in 2013 to 146.2 million sold units in 2015 (J’son and Partners Consulting, 2015) – numbers only representing the private-user market for wearables such as smart watches. Not considered in these numbers are mobile phones, wireless monitored health devices such as insulin pumps, blood pressure and heart rate monitors and many more. The engineering services company Libelium listed more than 50 applications (Libelium Comunicaciones, 2015) for using IoT-devices in a personal, semiprofessional or professional manner. For professional applications, such devices either are referred to as industrial Internet-of-Things (IIoT) or – according to their use-case – as smart metering, smart grid, smart production or smart-X, in general. Such smart-X systems can usually be characterized as networked sensors with communication capabilities – also referred to as a cyber-physical system (CPS) – sending its data for further processing, aggregation and evaluation to a cloud service. As mobile systems are very sensitive on their energy budget – typical capacities for portable LiPo-batteries used in wearable IoT-devices range from 1 to 5,000 mAh – may result in operating times from a few hours for smart phones to several days or few weeks for smart watches. This mainly depends on the processor load, measuring intensity, display operation and wireless transmission rate of a device. The Ragone diagram in Figure 1 shows the operating time of a typical mobile energy supply under full load as diagonal lines. The markers indicate the capacity of typical energy storages. Additionally, on the left-hand axis, the potential additional power as produced from autonomous energy sources is shown. This leads to the conclusion that energy is a very scarce resource for IoT-devices, and needs to be carefully managed. Apart from customer comfort, there are several – especially professional – use cases such as cargo-monitoring in a supply chain, environmental measurements for smart-city applications or long-term ECG monitoring for a patient with a heart disease, requiring very long and reliable operating times. But this increase in usability and customer acceptance often results in a severe lack of device- and data protection, and very insecure systems as additional computational loads have to be reduced to a minimum.