A Fog computing-based efficient data management smart home architecture

Smart home technology comprises of multiple devices communicating with each other and human occupants to provide state of the art living conditions. The increased use of smart devices in smart homes, increases the rate of energy consumption. Among the plethora of smart devices within a smart home, one of the key smart devices that account for high data volume and rate of data transmission is the Closed-Circuit Television (CCTV) surveillance system. Furthermore, there has been multiple attempts by researchers to use Cloud computing solution to address the issue of storage and processing capabilities. However, the use of Cloud computing has challenges such as energy consumption, latency, and network bandwidth usage bottlenecks with energy cost set to increase by April 2022. The introduction of Fog computing as a solution aim to address existing Cloud computing issues such as energy consumption, latency, and network bandwidth usage, providing improvements to mobility, security and on demand requests. In this paper, Fog computing will provide a method that supports the management of data generated by CCTV camera system while reducing the energy consumption, latency, and network bandwidth usage. The work presented in this paper demonstrates efficiency and optimisation of energy consumption, latency, and network bandwidth usage using iFogSim2 network simulation toolkit. A comparison and interpretation of results from the iFogSim2 output for Cloud and Fog based scenarios is used to evaluate improvements in energy consumption, latency, and network bandwidth usage demonstrating the benefits of Fog based scenario to efficiently manage data from the CCTV camera system.