# Range-Free Localization Approaches Based on Intelligent Swarm Optimization for Internet of Things
## 2 Related Works and Background
### Weight-Based Enhancements to DV-Hop
#### 2.1.1 Basic DV-HOP Algorithm
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Authors** & **Summary** & **Strength of** & **Anchors** & **Node Density** & **Localization** & **Approaches of** & **Complexity** & **Accuracy** \\ \hline \multirow{8}{*}{[PERSON] et al. in [25]} & A novel method that integrates & \multirow{8}{*}{Weighled redundancy} & \multirow{8}{*}{**Node Density**} & \multirow{8}{*}{**Localization**} & \multirow{8}{*}{**Approaches of**} & \multirow{8}{*}{**Complexity**} & \multirow{8}{*}{**Accuracy**} \\  & redundancy, optimized, becomes, and iterative techniques using hop & & & & & & & \\  & error-based signal weighting and an & & & & & & & & \\  & optimal average hop size to improve & & & & & & & \\  & localization & & & & & & & \\ \hline \multirow{8}{*}{[PERSON] et al. [30]} & An approach that involves modifying & \multirow{8}{*}{**Node density**} & Both static and mobile & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} \\  & the hop count technique and anchor nodes & & & & & & & \\  & the hop count computation is modified. & & & & & & & \\ \hline \multirow{8}{*}{[PERSON] et al. in [31]} & A modified approach that combines & \multirow{8}{*}{**Node density**} & Uses the PSO and SA & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} \\  & Particle Swarm Optimization (PSO) and & & & & & & & \\  & Simulated Annealing (SA) to handle & & & & & & & \\  & nonlinear equations. & & & & & & \\  & nonlinear equations. & & & & & & \\ \hline \multirow{8}{*}{[PERSON] et al. in [32]} & EDU-Hop combines an enhanced & \multirow{8}{*}{**Node density**} & Uses PSO with four & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} \\  & DV-Hop algorithm with Differential & & & & & & & \\  & Evolution (DE) to correct inaccuracies & & & & & & \\  & caused by the average hop size in the & & & & & & \\  & network. & & & & & & \\ \hline \multirow{8}{*}{[PERSON] et al. in [35]} & A localization approach called & Transformation vector & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} & \multirow{8}{*}{**Node density**} \\  & LSVD-HQ that leverages the least & & using the & & & & & \\  & squares theory to enhance the precision & & & & & & \\  & of node localization. & & & & & & \\ \hline \multirow{4}{*}{[PERSON] et al. in [34]} & An online sequential localization & \multirow{4}{*}{**Node density**} & \multirow{4}{*}{**Node density**} & \multirow{4}{*}{**Node density**} & \multirow{4}{*}{**Node density**} & \multirow{4}{*}{**Node density**} \\  & algorithm based on the DV-Hop & & & & & & & \\  & technique. & & & & & & \\ \hline \multirow{4}{*}{[PERSON] et al. [35]} & An approach based on a novel method & Uses a new average & \multirow{4}{*}{**Node density**} & \multirow{4}{*}{**Node density**} & \multirow{4}{*}{**Node density**} & \multirow{4}{*}{**Node density**} \\  & for hop size distance calculation with 2D & & & & & & & \\  & hypercubic techniques. & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comprehensive summary of DV-Hop localization algorithm variants.