### Fundamentals and Motivations  
UIoT devices and their types are discussed above in Section 1. In addition, the behavior of UIoT devices is smart sensing, highly mobile, heterogeneous functionality support, random selection in routing, etc. This causes, high energy consumption in UIoT environment. Moreover, the energy consumption in UIoT devices also depends on sensing, medium type, and depth, etc. Due to constrained underwater conditions, it is difficult to replace or recharge the battery of UIoT devices; this may reduce network lifetime or data loss in UIoT networks. Therefore, in order to increase the battery lifetime, network lifetime, and performance, etc., in UIoT networks, it is necessary to adopt various energy optimization techniques in UIoT devices. Figure 1: UIoT core applications, devices, and communication technologies. Figure 2 shows the perceptions of energy optimization in UIoT networks. As demonstrated, the energy optimization in UIoT comprises of three phases: energy efficiency, energy procurement, and energy generation. Energy efficiency carries the procedure to provide efficient communication by supporting less energy consumption, eliminating energy wastage, reducing energy demand, and lowering cost; energy procurement delivers the quality of service to the customer by proving fixed price, timely delivery of UIoT services, and cost-reimburse, etc. ; energy generation delivers the efficient methodology to generate energy in UIoT networks such as recharging with solar energy, recharge with underwater particles, recharging seawater spices, and recharging with fast waves, etc. In recent years, numerous routing and medium access control (MAC) protocols have been proposed to solve the energy optimization issues in UIoT. For example, [PERSON] et al. proposed an energy-efficient routing protocol selection for cluster-based underwater wireless sensor network (CUWSN) [3], [PERSON] et al. proposed reliable energy-efficient pressure-based routing protocol (RE-PBR) for underwater wireless sensor networks [4], [PERSON] et al. proposed a novel dynamic firefly mating optimization inspired energy-efficient routing scheme called FFRP [5], [PERSON] et al. proposed a multi-channel collision avoidance MAC protocol (MC-MAC) for underwater acoustic sensor networks [6], [PERSON] at al. proposed a joint energy-efficient MAC and routing protocol termed EE-UWSNs for underwater wireless sensor networks [7], [PERSON] et al. proposed energy-efficient MAC protocol termed bidirectional multi-flow MAC convention (BMF-MAC) [8], [PERSON] at al. proposed a novel energy-efficient contention-based MAC protocol for hybrid acoustic-optical networks in UIoT [9], etc. Despite the fact that several energy-efficient protocols have been developed, energy consumption is still a concern for UIoT due to the lack of developments, limitations, and behavior of each communication medium. Furthermore, most protocols are proposed only for acoustic-based communication technology with a simulation environment. Additionally, the technical limitation of UIoT networks, such as attenuation, channel noise, node mobility, and dynamic topology formation, etc., can reduce the battery life of UIoT devices. Therefore, energy optimization is still a concern for UIoT networks. Table 1 highlights the summary of the most recent routing and MAC protocols that deliver energy-efficient communication in UIoT. Figure 2: Energy optimization in UIoT. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Category** & **Year** & **Author, Reference** & **Protocol Type** & **Application and Methodology** & **Advantages and Limitation** \\ \hline \multirow{8}{*}{2011} & \multirow{8}{*}{2011} & & \multirow{8}{*}{Power-efficient routing protocol} & \multirow{8}{*}{*} & Proposed the simulation environment for underwater wireless sensor & \multirow{8}{*}{*} & Excellent performance in the case of battery consumption, packet delivery ratio, and end-to-end delay.