## 2. TYPES of Virtualization  
### Sensor Virtualization  
Sensor virtualization is a technique that enables multiple applications to operate in a virtual environment, and isolate applications from the hardware. The isolation is made by the middleware creating multiple logical instances of the physical sensor node. Multiple instances of a sensor node are made according to the capabilities of the sensor node, _i.e._, the service provisioning, processing power, memory on board and radio support. WSN virtualization aims to accommodate multiple logical network instances over a single physical network infrastructure with the ultimate goal of supporting applications with different requirements both in terms of nodes and communication functionalities. Furthermore, the network resources are utilized in a cost effective and efficient way [19, 20, 21, 22, 23, 24]. Physical or actual sensing is attained by the direct measurement of the physical phenomena. However, it is not necessary to gather information from a particular physical sensor it can also be an intimating contact sensor. This reduces the fault in the measurement and minimizes the errors [25]. A virtual sensor emulates a physical sensor, or it could be expressed as a software sensor that hides the hardware sensor. Virtual sensors provide indirect measurements of data by combining data from different heterogeneous physical sensors in order to provide services to the user [3]. Figure 2 shows physical sensor and the virtual sensor layer. A physical sensor can have multiple virtual sensors; however, it depends on the physical parameters of the sensor node, like processing power, on board memory and sensing capability. Virtual sensors layer lies on top of the physical sensor nodes. Furthermore, it decouples applications from the physical sensors, by running the applications on the virtual sensors. Physical sensors and coupled hardware are costly; they are sometimes erratic and need to be maintained. Moreover, physical sensors cannot be deployed on every site that needs to be sensed. Furthermore, virtual sensors' another advantage is that the sensed data at one location can be used to predict the current and future conditions of another location. The areas already deployed with the sensors can be monitored by the real time data monitoring, the same data when transmitted to the server is then processed to predict the situation in the areas not having sensors. The example in this regard is the flood and traffic monitoring systems. The sensor virtualization technique allows the user to obtain preferred and precise information in a more efficient manner from a limited number of sensors. Furthermore, this helps in reducing the energy consumption and cost of the overall network. Virtual sensors have a number of advantages in scenarios like replacing or maintaining a sensor node. Virtual sensor provides continuous data to the user, although the sensing mechanism of the node is discrete, and is at high time intervals in order to save the battery life. Furthermore, predicting output using techniques like artificial intelligence, in case of a physical sensor malfunctioning and failure. Moreover, virtual sensors provide significant advantages as they can facilitate multiple applications [26]. Using this approach, a better administration at node level and enhanced usability can be achieved by an increased number of different end users gaining access and control in sensors' information according to their needs and goals. Figure 2: Sensor virtualization and virtual sensors. The virtual sensor network formed may use any radio protocol. Virtualization brings flexibility in network administration, reconfiguration and scalability. Furthermore, virtualization of sensor network brings a high level of trust and security by logically separating different sensor and imposing security policies [27]. Figure 3 shows the multiple applications like _application1_ and _application2_ that can be facilitated by a number of services like _S1_, _S2_, _S3_, _......._, _Sn_.