Fog computing adds power to current cloud computing systems by including a localized computing architecture for data storage, processing, and computation.
Organizations, in the past, had to download software on their personal computers if they wished to run any program. Soon, IT experts realized that this kind of computing was lacking in various areas. Right from flexibility issues to concerns around disaster recovery and increased capital expenditure, this method was recognized to be insufficient in every aspect. Realizing this, IT experts came up with a solution -- cloud computing. With cloud computing, organizations were able to place every application or program on the Internet. Anyone could remotely access any kind of program, which increased collaboration among employees, efficiency at work, and shared control over information. The arrival of cloud computing not only benefitted businesses but also transformed the way individuals carried their daily activities. For example, checking your bank balance was never so easy as it is now, was it? However, despite the many obvious benefits, cloud computing opened up new challenges for businesses. With the increase in the IoT devices, cloud implementation fails to compute data at a fast rate. There was a need to have a computing infrastructure that is much closer to the data source to process the data as soon as the need arises. Due to the main program being on the cloud, organizations have to wait until the data streams back and forth between endpoints and the cloud for data-centric operations. Due to this, the overall network efficiency and performance deteriorates, severely impacting business operations. Hence, filling this technological gap was important to achieve better results in terms of network efficiency even with mass connectivity. Here’s where the concept of fog computing comes in.
As cloud computing systems are unable to efficiently compute and process the massive amount of data that is generated in today’s multiple data sources, fog computing can be a potential lifesaver. Before learning how, let’s first understand what fog computing is all about. The need to power up cloud computing was felt in the year 2012. Realizing that the high volumes of data that is generated on a daily basis requires low-latency processing, Cisco in the year 2015, coined the term ‘fog computing’ -- an improved and extended version of its ancestor, cloud computing. Basically, fog computing is a decentralized computing system that places the collected data either close to the data source or somewhere near the remote cloud servers. The advantage of this kind of computing is most of the data get analyzed and processed at or near the edge of the network. Due to this, the cloud computing method will not be required to process the same amount of data that it used to compute earlier. As a result of this, the overall network bandwidth will be optimally utilized.
Now that we’ve explained how fog computing deals with the tremendous volume of data that is generated from IoT devices and big data analytics let’s look at the benefits that businesses can reap from it.
One main issue that businesses had to deal with while using cloud computing was latency. If the time required for the data to reach the receiver's end is great, then it can not only reduce customer satisfaction levels but also can lead to potentially life-threatening situations. Take, for instance, self-driving cars. Various sensors implanted on a driverless vehicle generate massive amounts of data in real-time. This data has to be analyzed and processed almost instantaneously after being sent to the cloud. Delayed data transmission can pose serious risks to people traveling in the vehicle. Fog computing can be useful at dealing with slow on-cloud computational process. As fog computes the data on a server that is closer than the centralized data center, data transmission will become quicker, thereby eliminating the latency issue.
Fog computing is a decentralized computing infrastructure, which means that the servers are placed at various strategically determined locations. Such complex systems can be challenging to hack and disrupt. Hence, introducing fog computing can help organizations to bolster their cybersecurity mechanisms, thereby enhancing security for their IT environment.
The ultimate goal of every business is to provide unparalleled services to customers. As, due to fog computing, the ‘lag’ in data transmissions is minimal, customers can enjoy prompt response and assistance for all their requests. Such support will improve customer satisfaction and enhance their overall experience.
So far, we have explained the concepts of fog computing, what it means, and how businesses can benefit from it. Now, let’s run you through some specific examples of where and how fog computing can be applied in practical use cases:
One main challenge for smart cities is to analyze and compute the amount of data that is generated every second from millions and millions of sensors embedded throughout the city. Hence, smart cities can offer the right environment for implementing fog computing. Fog nodes are meant to process the data that is immediately required without sending everything back to the cloud servers. This being the case, the time taken for data to travel will be negligible. This means that the necessary actions will be taken in real-time, thereby helping the government and city developers to make the concept of smart cities a success in reality. For example, sensing the arrival of ambulances and changing the traffic lights to green automatically can save numerous lives.
There has been a tremendous buzz around drones for quite a while now. However, the concept of drones is still more theoretical than practical. The reasons for why drones haven’t reached mass adoption range from inadequate safety to bandwidth and latency issues. All of these issues can be fixed easily with the help of fog computing. With fog computing, drones can be monitored and handled by users. When a drone is in transit, constant monitoring is necessary to ensure that collisions don’t occur. Tracking the location and condition of drones in real time requires satellite links, which can be expensive for companies. With fog computing, the data that is generated will be processed in real-time, thereby eliminating the bandwidth bottlenecks and promoting cost savings. Besides, the minimal, almost negligible delay in computation will help companies know the current status of drones and take necessary measures during emergencies. For example, in instances when there are sudden weather changes, fog nodes will provide awareness and rerouting options, thereby ensuring drone safety.
Fog computing, which is seen as an extension to cloud computing, does not only minimize latency but also ensures security and privacy while providing intelligence through analytics in real-time. With fog computing, businesses can expect total awareness of and prompt response to any event, which can ultimately lead to increased business agility and improved efficiency. Thus, fog computing can be one of the best solutions to deal with exploding data volumes.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.