## 3 Novel Taxonomy for SSNs
### High Level Virtualization
#### 3.2.1 HLV Using Network Level Virtualization
The IoT-VN approach explores more general cases than MENO, as can be seen in Figure 22. The figure is partitioned, as follows:
* Partitioning IoT-VN partitions a subset of the available sensors in the sensor network. * Aggregation IoT-VN combines several sensor networks into one big VSN. * Extended IoT-VN includes non-constrained devices. (d) Hybrid IoT-VN combines partitions from two separate sensor networks and extends them with remote non-constrained devices. * The cooperating members of IoT-VN are connected using virtual links, that use an IDRA framework [56] to implement neighbor detection and tunneling mechanisms. To realize network packet processing for non-constrained devices it uses a click modular router [57], a C++ based framework is also used for routing data over the virtual links, they developed the AODV protocol to be extended to include IoT-VN ID header and network header. To study the performance of IoT-VN they built small networks of constrained and non-constrained devices, and run a simple ping application. The results demonstrate that it is feasible to realize IoT-VN approach in including resource-constrained and non-constrained devices in one virtual network. It still requires much more study to find out its actual performance under different and more complex applications. * **Multi-Agent System (MAS)**[58]: this approach proposes a solution for two main issues in VSN, they are creation and maintenance, and it proposes intelligent hibernations and offline operations for a sensor node when it joins more than one VSN. A Multi-Agent System is resident on individual nodes to facilitate the practical operation of adaptive VSNs, while ensuring optimal energy consumption. MAS is an agent-based solution that is built on top of Java SunSpot devices  
Figure 21: Layered Managed Ecosystems of Networked Objects (MENO) Concept. Figure 22: Internet of Things Virtual Networks (IoT-VN) generic cases. and is based on Agent Factory Micro Edition (AFME) library to create multiple agents on nodes (connectivity agent, coverage agent, hibernation broker agent, etc. ), as shown in Figure 23. It allows for message exchange between them based on VSN requirements and agents in each senor node can communicate with their peers on other sensors in the same VSN to optimize the performance of VSN creation and maintenance. To overcome the drawbacks of earlier layered VSN agent-based solutions with power management, inflexibility, homogeneous timing constraints, and co-operation with hibernating layers, the MAS approach provides a hibernation broker that organizes the sleep periods for each agent and it decides the hibernation process for some or all of the components of a node, depending on the requirements of active VSNs. The performance evaluation of MAS approach not studied in this article. * **A Resource Efficient Approach for Concurrent Applications**[59]: This article presented two real world applications to explain the concept of VSNs over the SSN, they approached geographically overlapped sensing applications and underground contaminant plume tracking; the first set of applications are for monitoring different events under spread heterogeneous WSN nodes over a large area and the second one is for tracing a dynamic event with a resizable subset of WSN nodes. A design for dynamic VSNs' creation has been proposed based on two main functions; node membership maintenance and maintenance, the first function handles node membership (adding, deleting, joining, leaving, etc.) and then implements the assigned tasks, but the second one handles data routing among the nodes, which may need the help of nonmember nodes to route the gathered data through the SSN to the desired destination.