## 3 Principals of Routing Protocols and Their Breakdowns
### Data-Based Routing Protocols  
Each component of the company has a clear goal of sending information. The Hub area is utilized as the basis for hub differentiating proof and steering in traditional directing conventions. During the transmitting stage, a small sensor organization is required to distinguish between information data in the district and information data in a single hub. When an event occurs, the hubs within visible reach become aware of it and begin gathering data, which they subsequently send to the sink hub to be prepared. Information-based steering conventions use data from the source hub to the destination hub to determine the optimum route during the journey. Figure 7 describes the taxonomy of the data-based routing protocols.  
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Classification** & **Protocol Year** & **Key Idea** & **Advantage** & **Disadvantage** \\ \hline Location-based & QLACO (2020) & Combines ML and ACO to improve the delivery ratio, delay time & High delivery ratio, and energy efficient & The role of ALV was not discussed in the paper \\  & ESRVR (2019) & Avoids routing hole using two-hop neighbor information & Scalable, and void hole detection & Few nodes take part in packet exchange, so those exhaust faster \\  & VBF (2006) & Uses a virtual pipeline to deliver the packet & Robust transmission, and scalable & Unbalanced energy utilization \\  & GEDAR (2016) & Depth-adjustment control by recovering void nodes & Void avoidance & High end-to-end delay \\ \hline Pressure-based & HYDROCAST (2015) & Avoids hidden terminal problem and minimizes co-channel interference & Less redundant transmission, and void detection & Nodes closer to the sink get exhausted faster \\  & VAPR (2013) & Uses greedy forwarding for selecting the next hop and constant beaconing & Detects and avoids void regions & High energy cost \\  & ACAR (2020) & Use of ant colony for path selection along with an acceptance factor for better delivery ratio & Less delay and better lifetime & Complex computation due to added acceptance factor \\ \hline Adaptive-based & MA-RF ARP (2019) & Uses modulation to improve transmission capability & Combines both acoustic and RF waves in transmission & Not suitable for harsh underwater environment \\ \hline Sender-based & RDBF (2014) & Adds fitness to the forwarding node for better delivery ratio & High delivery date & Complex computation \\  & RMTG (2010) & Pairs greedy forwarding along with knowledge of the previous hop to minimize the overhead & Void avoidance, Less overhead & Not suitable for sparse network \\ \hline Cluster-based & EERA-CA (2015) & Energy efficiency pairing clustering and special nodes & Energy efficient & Special node adds computation complexity \\  & CMSER 2019) & Use of clustering paired with shortest path to maximize energy efficiency & Increases the link quality among nodes & Special node adds computation complexity \\  & MRP (2014) & Using layering to eliminate localization & Use of super node to eliminate delay and localization & Unbalanced Power consumption, \\ \hline \hline \end{tabular}
\end{table}
Table 16: _Cont._  
Figure 7: Taxonomy of data-centric routing protocols.  
* Protocols Addressing Direction  
According to the specific approach described in the protocols addressing direction awareness, the sensor nodes pick the optimal next hop to send data. These direction aware routing methods are primarily concerned with data transmission efficiency. The following is a detailed description of these protocols.