# Mathematical Models for Named Data Networking Producer Mobility Techniques: A Review
## 3 Recent Mobility Techniques
### Anchorless Technique
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Ref** & **Technique** & **Simulation Tools** & **Parametric** & \
\begin{tabular}{c} **Advantages on** \\ **Performance** \\ \end{tabular} &
\begin{tabular}{c} **Weakness on** \\ **Performance** \\ \end{tabular} \\ \hline
[78] & \multirow{4}{*}{Anchorless} & mini-NDN & Cost metric & \
\begin{tabular}{c} The simulation has \\ improved network cost \\ metrics. \\ \end{tabular} &
\begin{tabular}{c} The experiment is only \\ suitable for single \\ gateway but not for \\ multi-gateway \\ \end{tabular} \\ \hline
[79] & \multirow{4}{*}{Anchorless} & ndnSIM & \begin{tabular}{c} Handoff and packet \\ loss \\ \end{tabular} & \begin{tabular}{c} The simulation results have \\ reduced handoff and \\ packet loss \\ \end{tabular} & \begin{tabular}{c} The experiment has \\ increased on end-to-end \\ \cline{1-1} \cline{3-5}  & & ndnSIM & \begin{tabular}{c} Handoff and packet \\ loss \\ \end{tabular} & \
\begin{tabular}{c} The simulation results have \\ reduced handoff and \\ packet loss \\ \end{tabular} &
\begin{tabular}{c} The experiment is only \\ suitable for single \\ gateway but not for \\ multi-gateway \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 6: _Cont._ \begin{table}
\begin{tabular}{c c} \hline \hline
**Technology and Application** & **Advantages** \\ \hline \multirow{4}{*}{Integration with 5G/6G networks} & Integrating NDN hybrid mobility with 5G/6G networks can enhance performance and efficiency. The 5G/6G networks provide fast data transmission speeds and minimal delay, enhancing NDN hybrid mobility’s efficiency. In addition, NDN hybrid mobility can alleviate the burden on the 5G/6G network by facilitating the caching and retrieval of data from intermediate nodes. \\ \hline Support for edge computing & \begin{tabular}{c} Edge computing involves utilizing computer resources at the network \\ edge to process data locally instead of transferring it to a distant data \\ center for processing. Integrating NDN hybrid mobility with edge \\ computing enhances efficiency and decreases the delay in retrieving \\ data in mobile and wireless networks. \\ \end{tabular} \\ \hline Integration with blockchain technology & \begin{tabular}{c} Utilizing blockchain technology enables secure and verifiable data \\ authentication in NDN hybrid mobility. It guarantees the genuineness \\ and uncorrupted nature of data while facilitating meticulous control \\ over data access. \\ \end{tabular} \\ \hline Support for vehicular communication & \
\begin{tabular}{c} NDN hybrid mobility facilitates inter-vehicle communication, \\ enhancing transportation networks’ efficacy and security. \\ Vehicle-to-vehicle communication facilitates data exchange regarding \\ traffic conditions, road hazards, and other elements that may \\ impact driving. \\ \end{tabular} \\ \hline Integration with machine learning and artificial intelligence &
\begin{tabular}{c} Integrating NDN hybrid mobility with ML and AI can enhance the \\ network’s performance. It enhances the efficiency of data routing, \\ forecasts user behavior, and detects potential network issues. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Technology and application based on NDN hybrid mobility. ity, which involves integrating NDN mobility with other layers of the networking stack, such as the transport and physical layers. Furthermore, integrating NDN mobility with Software-Defined Networking (SDN) can facilitate the implementation of real-time network adjustments and data flow optimization. NDN diverges from conventional IP-based networking by embracing a content-centric methodology. It employs a naming and addressing system, directly identifying and referring to content, redirecting attention from the source and destination IP addresses to the content. This paradigm shift enables data retrieval to be more efficient and adaptable.