In many applications of wireless sensor networks (WSN) the critical problem is efficient utilization of battery power to extend network lifetime . Most papers in the literature concentrate on energy efficient communication protocols at the network level. These protocols take into account communication model, network structure and topology, reliable routing schemes [17,18,19,20,21]. An important issue is also detailed energy consumption analysis at the network node level (neglected in the literature) which is the goal of our studies. Moreover, it provides additional information for protocol optimization.
Over the years, a large number of MAC-layer protocols have been developed for use in WSN, e.g. B-MAC , A-MAC , RI-MAC , X-MAC . Many studies in the literature compare the characteristics of these protocols focusing on a specific group. Doudou et al.  have reviewed asynchronous MAC protocols dedicated for time critical WSNs. Carrano et al.  have created a survey of duty-cycling mechanisms, dividing them into: synchronous, asynchronous and semi-synchronous. Huang et al.  have presented the evolution of MAC protocols over the years.
The technologies used in WuR and their parameters have changed in recent years. In particular, parameters such as sensitivity and energy consumption, have been significantly improved. Hence, WuR becomes attractive to be considered in WSNs. Blanckenstein et al.  have surveyed low-power transceivers and relate their characteristics to requirements for different application areas. Piyare et al.  have given a review of the research progress in wake-up radio (WuR) hardware and relevant networking software. In the sequel we discuss basic features of the cited WSN protocols. In particular, we focus on power consumption and transmission latency problems.
Duty Cycle Schemes
Transceivers used in WSN nodes usually employ FSK or PSK modulation variants. Despite significant progress in reducing energy consumption, the radio unit consumes typically 15–50 mW while listening to the radio channel. Assuming that the node is constantly listening for the upcoming transmission (5 mA) and that it is powered by 2xAAA batteries (about 750 mAh), the lifespan of such a node is only 150 h, which is definitely below expectations. When designing WSN consisting of nodes with limited resources and battery-powered, we expect maintenance-free operation for at least 5 years. Therefore, the node must temporarily turn off its radio in order to reduce energy consumption and ensure adequate lifespan. The technique in which the nodes go periodically into sleep and wake up only for a short period is called duty-cycling. The most popular is a scheduled duty-cycling, in which nodes wake up at the scheduled time, so the transmission can take place only when the active time arrives. Another approach is presented by the on demand technique, which is based on the idea that the node can be awakened when necessary. It usually relies on another communication channel. The proposed duty-cycling taxonomy, which includes on demand wake-up radio approach is shown in Fig. 1.
The main problem of using the scheduled duty-cycling technique is the delay in the frame delivery to the target node and as a result end-to-end delay. Moreover, choosing the optimal time between subsequent awakenings is always a compromise between energy consumption and delay in the frame delivery. Ensuring communication between nodes, that are inactive most of the time, requires an additional energy related to the following issues:
Overhearing The node receives a transmission that is not intended (or no longer useful) for it.
Over-emitting The node sends data while the destination node is not ready to receive it. This does not happen with synchronous protocols, but only with asynchronous ones.
Idle-listening The node listens when other nodes do not send.
Synchronization Nodes send sync messages to ensure mutual synchronization. This applies only to synchronous duty-cycle.
Depending on how a sender joins its target receiver, scheduled duty-cycling technique can be synchronous or asynchronous. In the synchronous approach, neighboring nodes are synchronized to wake up at the same time. The synchronization can take place using internal or external synchronization sources, see Sect. 3. In internal synchronization, nodes periodically exchange synchronization messages, which requires additional energy. While using external synchronization, the number of possible synchronization sources is very limited and the node requires more complicated hardware. On the other hand, in the asynchronous approach node clocks are independent which eliminates synchronization overhead but can significantly increase the amount of energy needed to meet the active period of another node. Moreover, the synchronous protocols are heavily affected by clock drift , while asynchronous protocols do not experience this effect. In asynchronous rendezvous, the node has no knowledge of awakening time of the neighboring node and therefore must turn on its radio and remain active to ensure communication when the neighbor is active. The node can wait for an adjacent node either by broadcasting or listening depending on the technique used.
Initially, MAC protocols based on asynchronous rendezvous used sender-initiated low power listening (LPL) to reduce energy consumption on the receiver side. B-MAC  is the first LPL protocol in which a sender starts transmitting a long preamble to meet receiver. The over-emitting and the overhearing effects are significant drawbacks in their practical use. The communication channel is occupied by the transmitter during the entire preamble phase, making it impossible for other senders to communicate effectively. X-MAC  and other subsequent LPL based protocols limit these effects. The over-emitting effect reduction is possible by applying a strobed preamble (multiple short preambles) and by sending an early acknowledgment (ACK). Nevertheless, this effect still remains the main limitation. The overhearing effect can be reduced using short preambles comprising target node ID so that the non-target receiver can quickly go back to sleep. In Fig. 2 (left), TX1 node initiates rendezvous by sending a strobed preamble (sequence of ID1s). The channel is occupied during the whole handshake procedure, hence TX2 node is not able to start transmission. The RX1 node to which the TX1 transmission is addressed sends a confirmation (ACK) as soon as it receives the preamble. TX1 starts the data transmission after receiving the confirmation. Due to the high channel occupancy, the use of LPL is limited only to applications in which the traffic load is low and the nodes transmit infrequently. According to EU harmonized regulations ETSI EN 300 220-2 (range 25 MHz–1 GHz), the channel can be occupied for only a fraction of time or a polite spectrum access has to be used. Similar regulations can be found in other countries, therefore LPL cannot be widely used in practical applications.
Another asynchronous technique is the receiver-initiated low power pooling (LPP). The advantage of the LPP design is that the channel is free for use before the target receiver is ready to receive. The idea of shifting communication initiation from the sender side to the receiver side is early presented in RICER . LPP for WSN was introduced in RI-MAC  and extended in A-MAC . Differently from the LPL, the sender instead of transmitting a preamble, waits for a beacon from the receiver and transmits the frame only after its reception. This substitutes the periodic beacons for the strobe preamble used in LPL, with the advantage, that the receiver beacon does not occupy the medium for as long as the sender preamble. In Fig. 2 (right), TX1 node is going to send data, therefore it listens to the channel while waiting for the beacon (ID1) from the target receiver. Both RX1 and RX2 nodes send beacons as identification messages but only if the channel is available (2nd ID1). As soon as TX1 receives beacon from the target node, it starts the current data transmission.
Moreover, it is worth noting that over the years, many protocols based on the LPL or LPP techniques have been tailored to specific applications . Numerous proposals use an adaptive approach, dynamically adjusting the node wake up time based on various network parameters. All these variations share a common problem which is a trade-off between energy consumption and delay. The use of an on-demand approach eliminates this problem, but requires the assignment and maintenance of an additional communication channel.
Wake-Up Radio Approach
The use of low-power wake-up radio (WuR) can significantly reduce the overall power consumption of the system. However, more importantly, it allows to reduce the delay in frame delivery to the target node, which is particularly important in delay-sensitive applications especially in Industry 4.0. The idea is to use an additional receiver with such a low power consumption that it will be possible to keep it active all the time. The main receiver will not be woken up periodically to listen to the channel, but only on demand in order to receive actual data. The energy consumption of WuR when compared to the main radio can be reduced by: energy harvesting, modulation technique, limiting sensitivity, limiting bitrate or using lower frequencies for wake-up triggering . WuR is not a new idea but in recent years it gains more interest. In 2017, 802.11ba standard task group (TG) was created as part of IEEE’s standard: IEEE Std 802.11 (i.e., Wi-Fi), to develop the WuR standard for wireless local area networks. This standard is expected to be approved in 2020, which will increase the availability of commercial WuR solutions. Ready-to-use WuR devices will help researchers to study practical applications, so new interesting results will emerge.
The WuR hardware design can be classified into active and passive approaches. The active WuR requires energy from external source e.g. battery. In contrast, the passive one harvests and powers the wake-up circuitry entirely from the RF signal, so it does not require energy from battery at all. Although passive WuRs are energy efficient and offer extended lifetimes, they have a much shorter operating range than active WuRs, typically only a few meters. Moreover, the process of accumulating energy also delays the wake-up of the main unit, affecting network performance by increasing latency. The active WuR addresses the constraints of passive one by increasing sensitivity and providing longer range with reasonable power consumption.
Over the years, various hardware solutions have been proposed and studied. There are several surveys [27, 28] that review presented proposals in terms of key characteristics of WuR technology such as power consumption, sensitivity and data rates. Most of the concepts use amplitude modulation in its binary form on–off-keying (OOK), only a few use a more complex one. OOK has the advantage of overall implementation simplicity which can be transferred into energy efficiency. Available solutions work in the subGHz or 2.4 GHz range.
Nevertheless, most of the WuR designers have opted to shift from high frequency to sub-GHz as an operating frequency for wake-up receivers. One of the reasons is that at higher frequencies the attenuation rate also increases, i.e., the 2.4 GHz signal fades faster than a sub-GHz signal. According to the Friis equation , the path loss at 2.4 GHz is 8.83 dB higher than at 868 MHz resulting into 2.76 times longer range for 868 MHz transceivers. The node with the main transceiver operating at 2.4 GHz with high sensitivity, e.g. 110 dBm can use WuR with lower sensitivity, e.g. 80 dBm, working at lower frequency to compensate power link budget. Moreover, lowering the bit rate allows to increase the signal-to-noise ratio (SNR) margin and consequently the range, unfortunately it extends the time (increases the energy consumption) needed to transmit a specific awakening sequence.
Besides the need for higher power for the same link budget, 2.4 GHz frequency band is more prone to interference due to spectrum crunch and devices such as Wi-Fi and Bluetooth operating in the same band. Sub-GHz ISM bands are mostly used for proprietary low duty-cycling links and are less likely to interfere with each other. This means easier transmission and fewer communication retries, which is more efficient and saves battery power.
An important issue is to compare power consumption of WuR networks versus duty-cycling schemes. Dealing with this problem we have developed power consumption models taking into account various parameters characterizing communication processes (Sect. 4). In these models we include also clock drift power cost which is neglected in the literature (Sect. 3). The analytical considerations have been used to compare WuR approach with duty-cycling schemes within a representative class of IoT networks (Sect. 5).
Precise timing is especially important in synchronous duty-cycling. Nodes communicating with each other must ensure synchronization between the start of transmission by one node and listening by the other one. Due to the limited accuracy of the clocks in the nodes, the network must provide a mechanism to synchronize the clocks in neighboring nodes . Broadcasting beacons is a commonly used mechanism to assure such synchronization. In this technique, one node, most often a coordinator, sends a beacon frame, which is a reference time point for neighboring nodes that synchronize their clocks. Depending on whether the synchronization takes place in the whole network, its part, or concerns only neighboring nodes, the frames are sent in a cascade within a given area or independently. Synchronization takes place periodically, with the period related to the maximum value of node clock inaccuracy. Adaptive solutions are also used, which determine the synchronization period for a group of nodes based on the actual rather than maximum clock inaccuracy values . The synchronization can also rely on a reliable clock source that is external to the wireless node. This could be a GPS receiver , the FM RDS signal  or national LF radio time signals, such as DCF77  which is available in Europe. However, these techniques are not widely used, mainly due to the complicated design of the receiver and additional energy consumption (as in the case of GPS) or limited coverage (as in the case of DCF77).
The choice of a real-time clock (RTC) oscillator operating in the sleep mode is always a compromise between energy consumption and accuracy, which creates an additional issue in synchronization. Let us consider nodes based on popular microcontroller chip CC1310. This chip has low-speed (LF) and high-speed (HF) clocks. LF clock is also available in STANDBY mode. The RTC is clocked from the LF 32-kHz RC oscillator (RCOSC_LF) or crystal oscillator (XOSC_HF). The RC oscillator consumes less energy but also has lower accuracy. The frequency accuracy of the Real Time Clock (RTC) is not directly dependent on the frequency accuracy of the 32-kHz RC Oscillator. The RTC can be calibrated periodically to accuracy within ± 500 ppm of 32.768 kHz by measuring the frequency error of RCOSC_LF relative to XOSC_HF and compensating the RTC tick speed. The accuracy of the RTC clocked from the crystal oscillator depends mainly on the crystal frequency tolerance and usually varies from 10 to 50 ppm. Additional software based calibration can be used to reduce clock drift caused by temperature changes.
Due to the clock inaccuracy, the nodes must take into account the maximum error and wake up in advance to enter the listening mode which results in idle listening. When synchronizing nodes using beacon frames, extending the time between successive beacons reduces energy consumption for exchanging frames, while on the other hand, it increases the energy consumption due to idle listening while waiting for data transmission.