Cloud computing and fog computing are often presented as alternatives, but the industry will likely see many IoT systems that are a hybrid of the two.
With millions of IoT connected devices, an enormous amount of data is being generated at lightning speed. As the data explodes, the cloud gets overused for data computation, management, and storage.
But, pushing workloads to remote servers for almost all data processing and storage has created many challenges like latency, reliability, network bandwidth, security, and more. The cloud server takes time to act on data as it functions as a centralized mainframe to store and compute data but is often located far away from the IoT endpoints. While it provides a centralized architecture, there is not enough bandwidth, and it costs too much money. This has led to the birth of fog computing to manage the burden of cloud computing services.
Fog computing has been dominating the IoT industry for the past decade, basically extending the cloud to be closer to the things that produce and act on IoT generated data. Its flexibility and ability to gather and process data from both the centralized cloud and the edge devices of a network make it one of the most resourceful and emerging technology to mitigate the information overload we face today.
The Benefits of Fog Computing
Fog computing provides organizations with more choices for processing data wherever required, producing better insights once the data is analyzed. It also enables organizations to take real-time actions on the analyzed data. Furthermore, it vastly improves security by handling more data at the edge and only sending what is really needed to the cloud.
Some of the main features of fog computing include wide-spread geographical distribution, low latency and location awareness, mobility, and scalability to include many nodes. These fog nodes process tasks without third-party interference and also offer computational flexibility, storage capacity, and better communication in the IoT continuum.
Since fog computing can run independently from the cloud, it allows the user to receive continuous, uninterrupted services, even if there is no network connectivity to the cloud.
Fog vs. Cloud Computing
Fog computing is frequently and often interchangeably used for the term edge computing. Though both provide the same functionalities in pushing both data and intelligence to analytic platforms near data sources, the key difference between edge computing and fog computing comes down to where the processing of that data occurs.
Fog computing has a few advantages over cloud computing. It can boost accessibility and usability in various computing environments. Shortly, cloud computing for IoT may fade away, but fog computing will take over. With IoT seeing an impressive growth rate, it needs a unique infrastructure base that can handle all its requirements, and Fog computing is the key to accomplishing this critical work.
The Future of Fog Computing
Fog computing provides solutions to a range of problems associated with cloud-based IT infrastructures.
Today, the data from millions of users, systems, and sensors that need to be stored, analyzed, and prepared for further processing is choking the bandwidth capacity and adding to latency. Adding on to that, specific government regulations and internal company policies of some companies ban the transmission of sensitive data over the network. To mitigate such requirements fog computing plays a key role in the IoT world.