## 2 Related Work
The above findings are the indicators of the necessity to devise novel mechanisms of trust and reputation assessment gives the idea of blockchain-enabled UASNs. The next section formally defines the specific problem of localization and its solution:  
* There is no technique at present which is a hybrid, jointly considering BC and the IoUTs as a BC-enabled Internet of Underwater Things (BIoUTs) for the trusted BNL problem with meta-heuristic techniques;
* There is no such job found that provides trust and reputation assessment in wireless underwater networks for secure BNL using BC;
* Better relationship management (in terms of data exchange) among node participants requires the absence of third parties. There is none of any idea has been found which enables BC at beacon level, i.e., the beacon nodes-oriented communication of the BNL problem;
* To ensure privacy and security of data transferred across hierarchical sensor beacon nodes without incurring excessive computing costs and requiring centralized control;
* There is no such work that facilitates the entire cycle of routing communication process of underwater among participants for trust and reputation assessment in solving the BNL problem by BC; \begin{table}
\begin{tabular}{c c} \hline \hline
**Symbols** & **Description** \\ \hline \(N_{B}\) & Populations of Beacon nodes \\ \hline \(N_{d}\) & Domination/elimination rounds \\ \hline \(N_{r}\) & Population response \\ \hline \(N_{c}\) & Firefly catching rounds \\ \hline \(F_{Pop}^{B}\) & Fitness of population of Beacon node \\ \hline \(\phi_{i}\) & Bacterium vector direction (randomly) \\ \hline \(\theta_{i}\) & Bacterium’s Platest position \\ \hline \(KS_{D_{s}}\) & Knapsack Dynamic equation \\ \hline \(Loc_{B}\) & Localization of B \\ \hline \(Loc_{B_{v}}\) & Localization of VBN \\ \hline \(Loc_{B}^{negl}\) & Localization of Beacon inside neighboring nodes \\ \hline \(E_{Cost}^{negl}\) & Cost of neighboring Beacon nodes \\ \hline \(B_{\pi}^{Trust}ON\) & Beacon’s Node trust value is ON \\ \hline \(BC_{Mis}^{Date}\) & Blockchain Miners against data transection \\ \hline \(F_{Pop}^{B}\) & Fitness of population of Beacon node \\ \hline \(F_{f}\) & Fitness function \\ \hline \(Pop\) & Population set \\ \hline \(Std\) & Standard deviation \\ \hline \(\theta_{i}\) & Bacteria’s latest position \\ \hline \(N_{B}\) & Populations of Beacon nodes \\ \hline \(N_{d}\) & Domination/elimination rounds \\ \hline \(N_{r}\) & Population response \\ \hline \(N_{c}\) & Firefly catching rounds \\ \hline \(N_{s}\) & Stochastic rounds \\ \hline \(KS_{D_{s}}\) & Knapsack Dynamic equation \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Nomenclature of algorithm symbols and equations notations. * There is no approach in the literature that applies BC at the beacon level to the BNL problem to assure localization while dealing with its dynamic, multi-level and heterogeneous character. It has been noted during the literature analysis, the proposed localization techniques are lacking the concept of inducing BC at this level such that it accounts for communication overhead, localization accuracy and preservation cost. Most of the localization methods and algorithms which were described earlier, such as [14; 15; 16; 17] and [19; 20; 21], which are implement localization at sink levels; however, [10; 12; 13; 17; 19; 20; 23; 27; 28] produce high localization accuracy while [8; 9; 14; 15; 18; 22; 24] have noticeable communication transparency. Furthermore, [12; 15; 23] ignore the high energy consumption ratio. In case of error estimation, [2; 4; 6; 7; 8; 10; 11; 13; 14; 15; 16; 17; 20; 23; 25] did not investigate their impact. However, [10; 12; 14; 15; 16; 19; 21; 22; 27] are good for maintaining energy and prolong the network lifetime. Moreover, [2; 3; 4; 6; 10; 12; 13; 14; 15; 16; 17; 19; 22; 23] are proven to be delay-oriented techniques. It is interesting to note that none the localization techniques/algorithms were previously tested with BC.