By: A. Dahiya
Cloud computing has caught the eye of both users and service providers as the most intriguing computing platform, a distinction that no other computing paradigm has achieved. Unlike on-premises IT, cloud computing provides computing resources like storage, applications, servers, and networking to the requested user irrespective of his geographical location. Scalability and availability of on-demand resources are the key features of cloud computing, making it the most preferred choice for users. However, it has some disadvantages too, like high latency, downtime, security, and privacy of the data. Figure 1 shows the concept of integration of cloud and fog computing for different services.
We have another computing paradigm that addresses these issues, namely fog computing. Fog computing brings cloud computing closer to the users by placing resources at the edge of the network. Here, one should note that fog computing is not the replacement for cloud computing. It is the extension of cloud computing where cloud capabilities are extended to the source of data as much close as possible. The key features of fog computing that give it an upper hand over cloud computing are low latency, reduced bandwidth, improved security, better user experience, etc. However, with some advantages, disadvantages also exist, for example, increased expenses as organizations have to buy more hardware like routers, gateways, etc., as edge devices. The second disadvantage is scalability, as the fog is not as scalable as the cloud.
Cloud and fog computing are dedicated to resource utilization, i.e., the cloud has been used for core resources, while the fog is used to utilize edge resources of a network. Both technologies have been immensely utilized in IoT. IoT is the huge network of devices like sensors, RFID tags, actuators, mobile phones, and laptops. IoT generates a huge amount of data from all over the regions in the world. Therefore it is very important to handle this data efficiently. Though the cloud can handle this enormous data, data flow to and from cloud data centers is a major issue due to bandwidth constraints. It is a nice practice to process the data where it is generated. So, fog computing provides an efficient solution to this problem.
There is no denying the fact that cloud and fog computing are not a replacement for each other. In fact, they complement each other and shield the drawbacks by their respective advantages. For an organization involved in IoT, where the data generated is in enormous amounts. Cloud has the potential to provide storage to the data, but it has constraints like latency, mobility, network bandwidth, security, privacy, and many more challenges. So, it is impossible to execute everything on the cloud. Nor we can execute everything at the edges of the network as large storage space cannot be provided by edge points. Fog computing is suitable for applications that are time-sensitive. Therefore, integration of cloud, fog, and IoT could provide energy-efficient services with higher performance, reduced latency, quick response time, scalability, and better localization accuracy.
The driving force behind IT development is the new requirements of evolving technology. The Internet of Things is a rapidly expanding sector that necessitates more efficient data transmission and processing methods. To make the most of emerging prospects and capture the actual potential of the technologies, businesses should analyze cloud vs. fog computing.
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Cite this article:
A. Dahiya (2021), Integration of Cloud and Fog Computing for Energy Efficient and Scalable Services, Insights2Techinfo, pp.1