## 1 Introduction
In this regard, it is worth considering making the C-IoT operate and work in a more energy efficient manner. In the literature, there are many research works investigating how to optimally utilize the system power resource and make the C-IoT more energy efficiently. Specifically, [PERSON] et al. in [22] investigated the density clustering-based base station (BS) status control algorithm to reduce total power consumption, where the number of active BSs and their locations could be determined. Similarly, Reference [23] put forward the approach for the BSs to control the on-off states of the IoT devices via downlink signaling. Furthermore, this paper addressed the issues of uplink power control for IoT devices, aiming to improve the uplink coverage performance. Apart from the aforementioned \begin{table}
\begin{tabular}{l l l} \hline \hline  & **Details** & **Disadvantages** \\ \hline \multirow{3}{*}{ZigBee} & 1. Standard low power protocol based & 1. Severe interference from a single channel \\  & on IEEE 802.15.4 & transmission \\  & 2. Enables low data rate & \\ \hline \multirow{3}{*}{Bluetooth} & 1. Standard wireless access technology & 1. Sensitive to fading and interference \\  & based on IEEE 802.15.1 & 2. Wide coverage results in a low data rate \\  & 2. Enables short-range transmission with & \\  & a data rate of 1 Mbps & \\ \hline \multirow{3}{*}{WiFi} & 1. Standard wireless access technology & 1. Poor mobility \\  & based on IEEE 802.11 & 2. Severe interference \\ \cline{1-1}  & 2. The most frequently used wireless & 3. Lack of security \\ \cline{1-1}  & access technology & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of the conventional wireless access solutions for MTC devices. research towards energy efficient C-IoT, there are also many papers talking about the energy harvesting schemes in the C-IoT. In [24], the authors studied the energy harvesting schemes for uplink and downlink coverage, and the time division-based method was adopted to enable power and information transmission. To realize sustainable communications for massive C-IoT, [PERSON] et al. designed an architecture for channel state information acquisition, signal reconstruction, information decoding, and energy harvesting [25], and the negative effects of channel uncertainty, successive interference cancellation, and non-linear energy harvesting on sustainable communications were also observed. Reference [26] investigated the self-sustainability of the overlay IoT, where the harvested energy was sourced from the downlink cellular networks. The authors in [27] studied the energy and spectrum efficient IoT network, where the spectrum was used for improving spectrum efficiency and energy harvesting. Moreover, the energy transfer was adopted to boost EE in this paper. For non-orthogonal multiple access (NOMA)-based C-IoT, which is equipped with the function of simultaneous wireless information and power transfer (SWIPT), Reference [28] investigated two beamforming designs to maximize the weighted sum rate and minimize the total power consumption, respectively. In light of the above, in order to solve the ubiquitous and seamless connectivity problem in IoT, we propose a three-plane C-IoT architecture, consisting of the device plane, the access and edge computing plane, and the cloud computing plane. Based on this architecture, we concentrate on the energy efficient and harvesting designs to implement green C-IoT. Specifically, the energy efficient schemes include efficient random access and barring mechanisms, self-adapting machine learning predictions, scheduling optimization, resource allocation, fog computing, and group-oriented transmission. The energy harvesting schemes are classified into two categories, namely ambient energy harvesting and dedicated energy harvesting. More details of these schemes will be presented in the following parts. The rest of this paper is organized as follows.