# A Study on the Design of Fog Computing Architecture Using Sensor Networks
## 5 Conclusions  
Cloud computing provides data content and control information to devices based on centralized data access and delivery structure. With cloud computing, a huge amount of data is transmitted and processed. There are also problems such as delays in service response time. In addition, as the Internet of Things develops, the application fields of sensor networks are further expanded, and demands for real time processing, transmission, and security of information controlling object Internet devices are increasing. Fog computing has emerged as a way to effectively address this problem. Fog computing is also referred to as edge computing, and includes a function of processing information collected from a device before sending it to the cloud to reduce the amount of transmission or performing itself without receiving device control information from the cloud. Thus, the data transmission delay in the device is reduced and the device can be controlled in real time.  
With the recent increases in the number of devices, the power consumption in the communication between the sensors in the fog computing environment is increased. Various studies have been  
Figure 14: Life Time Comparison of Devices.  
conducted to improve the performance in various scenarios and service delays in fog computing, but research on effective power reduction is insufficient.  
This paper presents a power consumption problem in the fog computing environment and suggests an effective method for power reduction. We also propose a method for securely managing the data generated by each sensor.  
In order to solve the power consumption problem, a proxy server is placed between the cloud server and the sensor, and the proxy server processes the data according to the frequency of use of the data, thereby reducing the load of the entire communication. In addition, effective power reduction is achieved between the proxy server and the sensor by hierarchically managing it according to power consumption. Experimental results show that the total network latency and network usage are reduced. The system encrypts data based on the user's attributes so that only authorized users can use the information. In addition, it performs efficient data management by adding attributes and revocation. As a result of verifying the problems that may occur in the process of withdrawing the attribute value of the user through the security evaluation, it can be seen that it is safe because the property value cannot be falsified or the attribute cannot be updated at random.  
Future research needs to be applied to a sensor network that can move freely in the proposed method through simulation. And intelligent data transmission methods based on information- centric networks using context-aware technology.  
[PERSON]. ([PERSON]) was to create the main ideas and execute performance evaluations by simulation. [PERSON] ([PERSON]) contributed to the simulation and provided detailed advice in the reviewing and editing of this paper. [PERSON] [PERSON]. ([PERSON]) improved the framework of this study and reviewed the paper.  
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2016R1D1A1B03931689).  
This work was also supported by the Dongguk University Research Fund of 2018.  
The authors declare no conflict of interest.