**2.3 Battery level**

The limit used is Battery level for HUB selection is as in **Figure 3**. Sensor nodes Used for WBANs have specific defined energy and power [9].

The sensor nodes can be utilized for a long time if energy is efficiently implemented. As the HUB requires more energy, a fixed hub will lose its required stamina if used for a long time at work. A sensor node is selected as a hub if it is ready to apply the maximum energy after the first sensor node failure, increasing the overall network lifetime.

#### **2.4 Priority of sensor node**

A priority of the sensor nodes in WBANs is considered as the parameter in the selection process for the new hub **Figure 4**. The highest priority is given to important vitals like EGG, EEG which transmit data quickly and a need to live for a longer period. In this selection process, the sensor node with the least priority is picked as a hub to transfer high packets.

### **2.5 SINR**

This is the new parameter utilized in our chapter to bring down the interface or disturbances in the network. There are various data traffics in WBAN's, for

**Figure 4.** *Priority sensor membership function graph.*

#### *Coding Theory - Recent Advances, New Perspectives and Applications*

**Figure 5.** *SINR range in the membership function.*

instance, merging of one signal with another or moment of a network from place to place. In wireless communication systems such as networks, SINR is used as the rate of information transfer representing the received signal strength. As the noise in the signal plays an efficient role in decreasing the data accuracy received at the receiver. Moreover, it is defined as the ratio of signal strength to the interference or noise of the signal. For communication link quality, SINR plays a pivotal role. SINR is used for identifying moisture and thermal noise at the sink, in wireless communication if any interference occurs at the data transmission, path loss takes space which results in great network disturbance. So, SINR is utilized to reduce this effect in data transmission.

This is also used to avoid interference in the affected sensor node. Then, a fuzzy-based membership function is used to calculate SINR ranges (0db to 12db, 12db to 20db, 20db to 50db) where the disturbance occurred due to the transmission period is sorted. In Telecommunication LTE measures the values in terms of powers of the signals that is considered as a standard value in wireless transmission of data. The SINR, greater than 20db is selected as HUB as shown in **Figure 5**. This is done by sharply bounded values in fuzzy-based logic for calculating the candidacy value, which decides the HUB using all parameters. The lowest noise signal reflects the highest valued SINR in quality of the network and interference.

## **3. Experimental results and analysis**

LabVIEW (Lab Virtual Instrumentation Engineering Workbench) is a software platform developed by national instruments for data acquisition, controlling, and automation using Microsoft windows, various types of UNIX, Linux Mac OS. It is widely applicable for its features like graphical representation which are highly recommended for engineers and scientists, where data flow can be known and each step can be monitored if required. It also consists of different libraries with different toolkits and the major advantage of this is it is easily configurable with hardware, mainly for processing. The programs operated in LabVIEW are known as Vis. LabVIEW is a geographical programming language to create block diagrams in a block diagram panel. This is a user-friendly environment made up of a front panel and block diagram as shown in **Figure 6** for the dynamic HUB selection process along with the fuzzy-based functions.

*Dynamic HUB Selection Process in Wireless Body Area Network (WBAN) DOI: http://dx.doi.org/10.5772/intechopen.98613*

**Figure 6.** *Block diagram of LabVIEW for dynamic HUB selection.*

The below-shown Figure represents the block diagram of the fuzzy-based system(the logic used) for selecting a HUB. Briefly, it collects the sensor data from the parametric values and processes an output by using fuzzy logic. For instance, two sensor nodes are first implemented on the front panel as shown in **Figure 7**.

In the front panel and block diagram, the input is given manually. The block diagram consists of loops and control lines where the flow of data virtually visible.

**Figure 7.** *Front panel code using 2 sensor nodes.*

**Figure 8.** *Candidacy membership function.*

The fuzzy system is an inbuilt library function in LabVIEW. The fuzzy system uses an engine to convert numeric data into crisp value as shown in **Figure 1** by implementing the bordered values through fuzzy rules and the output is shown in the candidacy membership function [10].

The Fuzzy output is taken and the common logic is used for a candidacy value with the highest based on the four parameters. The greatest Candidacy value will be considered as a new HUB, Which will be displayed in a string format in the LabVIEW front panel. This output is calculated as in **Figure 8** which considers the low(0–10), medium(10–20), high(20–30) range. Out of which the highest candidacy sensor node will be selected as a Dynamic HUB by using AND or OR functions.
