# A Web of Things-Based Emerging Sensor Network Architecture for Smart Control Systems
## 5 Performance Evaluation
### The Effect of the Proposed WoT-ESN Architecture  
In order to test the proposed WoT-ESN architecture under a heavy load, a number of home users generate several requests to check the details of a household appliance through the Web. The frequency of the request generation is set to one request per minute for each home user. In the proposed smart home architecture, the number of users is less than the number of household appliances. Therefore, the response time in such situations is negligible for various requests. However, we tested a scenario where a greater number of users and a smaller number of appliances is considered. Moreover, the requests are passed to the respective sensors via MS following the multi-hop architecture of IEEE 802.11n network, even if the information is available in the MS.  
This experiment is performed for 10 min in various scenarios. In the first test, the webpage is placed on a separate computer while the MS and sensors are present in a different computer. In addition, both the webpage and sensor and MS are present on a different network to check the performance of the multi-hop concept in the proposed scheme. As shown in Figure 3, the users are sending requests to three, five, and seven household appliances.  
The results reveal that as the number of requests increases in the case of two household appliances, the response time also increases. However, with the increase of the number of household appliances, the response time decreases.  
Figure 3: Response time analysis.  
The division of the requests in processes highly reduced the response time even if the requests are for the same household appliance. Moreover, each request is routed through different paths to check the effect of the multi-hop environment. Whenever the sensors are available at a closer distance to each other, there are greater chances of interference. Therefore, there is a high chance of failed attempts to send the requested data to the Web. In order to simulate a similar scenario, the sensor nodes available in the smart home scenario depicted in Figure 1 were divided into four groups. The groups 1, 2, 3 and 4 are available 3, 6, 9 and 12 m apart from each other. The group of sensors available 3 m apart from each other is highly affected by the interference and therefore, the failed transmission attempts in such scenarios are very high. The number of failed attempts when the number of requests reaches to 120/minute is more than 10%. However, the number of failed attempts significantly decreases when the physical distance between the sensors is more than 3 m. A similar scenario with three sensor nodes and multiple requests per minute is depicted in Figure 4.  
All the sensor nodes are operating in the same channel. It is clearly intuited from the results that the number of failed attempts are more than 3% of 120 requests/minute. However, these are the worst conditions, which is far better in real time scenarios by implanting the proposed scheme. The discovery time of all the sensors present in the smart home is computed as shown in Figure 5. Initially, the proposed system registers all the sensors node attached with each device in the Web server via the actuator and MS. However, if the number of sensors is more then it requires more time to load all the sensors into the framework. Therefore, it is very important to compute the discovery time of the devices present in the smart home.  
An experiment is performed on discovering 30 sensors present in the proposed smart home scenario. The experiment reveals that if 20 sensors are turned on and discovered at once, it requires around 19 s to fully connect with the framework. However, the discovery time increases if more than 20 sensors are turned on at once.  
Figure 4: Transmission failure analysis.  
Figure 5: Device discovery analysis.