## 3 Novel Taxonomy for SSNs
### High Level Virtualization
#### 3.2.3 An Insight on the Application of HLV  
This area of research is still considered to be recent, thus not much work has been done on it. Therefore, this section will provide us with the conclusion from studying virtualization in HLV, where Table 3 provides a summarization of some characteristics for each virtualization solution. Figure 34: WSNTB Design. Figure 35: Cyber-Physical Networking (CPN) Infrastructure. * Virtual Network/Overlay Sensor Networks solutions: The importance of these overlay approaches to SSNs is coming from the ability to transmit data between the nodes without the need to build a new infrastructure. Thus, the overlay approach is appealing to achieving the virtualization in SSNs. * Multi-layer architecture for VSNs: This three-layer architecture is based on overlay network virtualization, which provides scalability in all layers. It does not require the re-deployment of the entire network in the case of new agents. Application tasks are loosely coupled with the agent in the overlay network. Each application is implemented as an overlay; thus, a node can be a member of multiple overlays. Introducing a Gate-to-Overlay entity to support the legacy nodes at sensor layer provides two separate channels for data and signaling, which provides lightweight data exchange protocols between the interface layers. However, the complexity in building the Gate-to-Overlay node is found, since it will consume more energy and support more tasks that are related to the legacy nodes. * MENO: It is one of first trails to integrate the SSNs with the internet, network virtualization based on virtual links over layer 2 or layer 3 in traditional networks. It still a conceptual work. * IoT-VN: Network virtualization in this solution is based on the concept of MENO. It presents some implementation details regarding the integration between SSNs and the internet. Thus, it concerned with connection resource-constrained and non-resource constrained devices together and allows end-to-end communication for the deployment of applications and services. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Solution** & **Solution Type** & **System** & **IoT Support** & **Formation Concept** & **On-the-Fly** \\ \hline Multi-layer VSN & & & & & & \\ (2013) & & - & - & Data \& control paths & - \\ \hline  & & Embedded Linux for & & & \\ IoT-VN & & non-constrained & & & \\ (2012) & & devices & \& & \\ VSN & & TinyOS + IDRA for & & & \\ Overlay & & - & \& & \\ (2011) & & - & \& & \\ \hline MAS & & - & - & Multi-Agent System & - \\ (2008) & & TinyOS+ Maté & - & Dynamic grouping & \& \\ \hline Cluster Tree & & - & - & Dynamic Tree based on & - \\
2009 & & - & - & phenomena tracking & - \\ \hline Closed-Loop System & & & - & Phenomena-aware & - \\
2008 & & - & - & Clustering & - \\ \hline GENI & & - & - & Virtual Links & - \\ Life Testbed & & & - & - & Virtual Links & - \\ \hline FIT IoT-LAB & & & - & - & Virtual Links & - \\ Open access Testbed & & - & \& & \\ \hline WSNTB & & - & \& & Virtual Links & \\
2008 & & Participation & TinyOS+ Java runtime & - & \
\begin{tabular}{c} Cluster – gateway \\ Based \\ \end{tabular} & - \\ \hline CPN & & - & - &
\begin{tabular}{c} Cluster – gateway \\ Based \\ \end{tabular} & \& \& \\
2011 & & & - &
\begin{tabular}{c} Cluster – gateway \\ Based \\ \end{tabular} & \& \& \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Characteristics Summary of SSNs’ HLV Solutions. MAS: An agent-based network virtualization solution is presented in this approach. Although the main target is creation and maintenance of VSN, there are no details regarding VSN formation and its operation. * A Resource Efficient Approach for Concurrent Applications: Although it presents two real world applications shared the same SSNs, it does not mention any technical details for creating a dynamic or static VSNs. * Melete System: This system provides a dynamic logical grouping of sensors over the network to serve a certain application. A node can be a member of multiple groups.