## 2 Related Work  
There is a vast amount of literature relating to energy conservation to improve the lifetime of WSNs, as a plethora of methods and techniques has been proposed in the last few decades. As a result, there exist many surveys on energy-saving techniques in WSNs [9; 10; 11; 12]. However, energy efficiency analysis is complicated because the network lifespan depends on many aspects, including network infrastructure and technology, computational load, routing protocols, channel characteristics and energy consumption model. Sensor nodes consume energy during sensing, processing and communication. Many approaches proposed in the literature assume that the energy consumed by the sensor in the communication module is much higher than the energy consumed for data sampling or processing [11]. Therefore, energy-saving in WSNs is focused mainly on optimizing the operation of the radio module. In [9], the authors presented a taxonomy of energy-saving strategies that mainly concentrated on work cycling and data-reduction techniques. [PERSON] et al. [10] reviewed approaches that strive for prolonging the network lifetime by Topology Control (TC). They proposed a novel definition of Topology Control and categorized the relevant techniques into different classes. In a more recent survey [12], the authors provided a survey of the existing energy-saving approaches in the conventional static WSNs that are not fitted with any energy harvesting or movable modules. They also proposed a general definition of energy efficiency for stationary WSNs. The WSN topology is defined by the devices deployed in the environment and the links available between them. Links arise from the communication ranges of installed radio modules. By taking various actions, one can influence the network infrastructure and generate network topologies with desired characteristics (e.g., lifespan, robustness, coverage, connectivity) while increasing network capacity and reducing power consumption. Furthermore, energy-aware routing protocols can be em  
Figure 1: Application examples: the range and severity of toxic fumes may be approximated using selected sensors (left graph), the movement of an animal may be reconstructed by analyzing historical data collected by sensors (right graph). ployed to reduce transmission time and energy. To summarize, the following techniques can facilitate energy saving in WSNs: (1) transmission power control [13; 14; 15]--adjustment of the transmit power of the radio module to maintain a transmission range; (2) clustering and activity control [4; 16; 17; 10]--clustering of nodes into clusters and temporal activation and deactivation of sensory nodes; (3) energy-aware routing [18; 19]--calculating energy-aware routing tables, multi-path routing sink mobility; (4) energy-efficient data reduction [2; 3; 20]--aggregation and routing of data over a multi-hop network, processing data in intermediate nodes to reduce redundant data before transmission, adaptive sampling. The approach proposed in this paper belongs to Activity Control (AC) algorithms. WSNs typically consist of a large number of sensor nodes distributed in the environment. Sensor data is typically transmitted over some time, either according to a schedule or in response to a new event. Therefore, in most scenarios, communication modules can remain inactive most of the time and are only activated to transmit measurements or receive messages from other sensor nodes. This fact is particularly advantageous since transmission is expensive and the power consumption of the communication module depends on the current operating mode. Activity control or sleep/wakeup schemes utilize dynamic control of radio modules of all nodes and adjust the operating mode according to the current situation in the network to reduce power consumption and thus increase the network lifetime. Therefore, implementing an appropriate strategy for transitioning to different states is critical for effective idle power control.