# A Survey on Energy-Aware Security Mechanisms for the Internet of Things
## 2 Energy-Efficient IoT
### Existing Energy-Saving Techniques
#### 2.3.1 Hardware Energy-Saving Techniques  
* _Low-power microcontrollers._ Low-power microcontrollers in IoT systems considerably extend the battery life, making them ideal for applications that require long runtimes. Due to the fact that sensor nodes are often battery-powered in reality, lowering the energy consumption not only extends battery life but also reduces battery replacement needs, which in turn slashes the risk of environmental contamination when discarding old batteries [22]. Additionally, energy savings yielded by low-power microcontrollers help cut back the demand for power resources.
* _Energy Harvesting and Sleep Mode._ Energy harvesting technologies refer to the processes that capture and convert external energy sources into electrical energy. There exists a broad spectrum of external energy sources, including solar, mechanical, thermal, wind, water, radio frequency, etc. For example, solar energy-harvesting technologies strive to leverage solar cells to convert light energy into electrical energy, whereas radio-frequency energy-harvesting technologies harness radio frequency signals to perform electrical energy conversion. On the other hand, the development of sleep-mode technologies becomes essential to achieve long-term self-sustainability for IoT applications [23]. Taking a sensor node as an example, if there is no need for it to sense its target environment for a certain period of time, it can transition to sleep mode for energy-saving purposes. Likewise, its sensors can be transitioned to sleep mode if its battery power drops below a critical threshold. The transitions can be  
Figure 4: Existing energy-saving techniques.  
performed dynamically based on multiple factors such as the sensors' battery status and information quality. In short, energy-harvesting and sleep mode technologies help extend devices' life and enhance the energy utilization of IoT systems [24].
* _Power Management_. Advanced power-management techniques, such as power-curtailment strategies and dynamic voltage and frequency scaling (DVFS), can effectively diminish power consumption. Power-curtailment strategies (e.g., power-gating techniques) focus on reducing the static power consumption of digital circuits. The power consumption of digital circuits consists of two main contributors: dynamic power consumption and static power consumption. Dynamic power consumption refers to the power consumed when the circuit is switched, while static power consumption is primarily due to the leakage current of the transistors, which consumes power even when the circuit is not performing any operation [25]. The power-gating technique inserts control switches between different parts of a circuit such that the power supply to a block of circuitry will be cut off when the block has no task to perform, thereby reducing the power consumption of digital circuits [26]. As for DVFS, it is a commonly used strategy that dynamically adjusts the power voltage and clock frequency of processors. In particular, in underload conditions, DVFS lowers a processor's voltage and frequency to reduce the power consumption. Conversely, in overload conditions, DVFS increases the processor's voltage and frequency to provide necessary computing power [27]. This technique is especially critical for battery-powered mobile devices because it enables IoT devices to achieve the best performance-to-energy ratio under various workload conditions, thereby prolonging their service time. In brief, power-management techniques fine-tune the power supply to IoT systems, reducing the overall power consumption of IoT devices and extending the battery life of battery-powered devices.