While cloud computing is already a familiar concept among tech enthusiasts, fog computing is also making a mark in the industry. But, the tech industries and IoT have been using these for quite some time. Especially for IoT architecture, both computing models play crucial roles. Since these are getting increasingly popular, knowing the difference between fog and cloud computing is essential for business decisions and deployment.
What Is Fog Computing?
Fog computing is a part of cloud computing, and hence, these are interconnected. In the natural world, you will see that fog stays closer to the earth than clouds. Similarly, fog computing brings cloud capabilities closer to the end-users. As it was coined in 2014 by Cisco, the term and the concept is comparatively new to the common people. Fog computing uses an individual networking panel for data processing instead of using centralized cloud platforms. It allows users to store, calculate, communicate and process data by letting them access the entry points of various service providers. While cloud computing takes more time to respond timely to each query, fog computing makes the process lot quicker. It is a distributed decentralized infrastructure that uses nodes over the network for deployment. It also functions as a mediator that decides which information to process locally and which should be sent to the cloud.
Benefits of Fog Computing
Responsiveness
Fog computing brings the data storage and processing power closer to the user. Thus, businesses can achieve near-instantaneous results.
Cost-Efficiency
It also helps you by reducing your data processing cost. There is less bandwidth usage involved in fog computing, and no need to use expensive dedicated hardware at your network edge. All these contribute to a cost-efficient model.
Reduced Latency
It uses less number of hops for transferring data from its source to its destination. As a result, it helps to reduce latency.
Security and Privacy
It does not transmit your data to the cloud server. Hence, businesses can ensure less chance of data leakage.
Improved User Experience
Fog computing is also capable of offering a better experience to the end-using with features like instant responses and zero downtime.
Smooth Connectivity
Using fog computing means no complaints about the loss of connection. It uses multiple interconnected channels to ensure the best connectivity for any activity.
What Is Cloud Computing?
Cloud computing offers internet-hosted services to users according to their demands. Using it, one can access information regardless of geographic location. For data processing and storage, it depends on remote servers. In this model, software and files are not stored on a local hard drive. Instead, a network of connected servers is used to store and answer different queries. The availability of services from any place, anytime, makes it a highly popular service in the fast-paced technology world. Besides letting people collaborate and communicate in real time, it also offers fast and easy access to data. Whether it is sending large files to your friends or working on the same file with your colleagues, flexibility, and convenience are impossible to imagine without cloud computing.
Benefits of Cloud Computing
Convenient Pricing Model
To use the facilities of cloud computing, businesses can choose pay-as-you-go pricing. Thus, they have to only pay according to their usage.
Scalability and Flexibility
With cloud computing, you can scale up and down the resource and infrastructure usage according to your requirements. This offers unprecedented flexibility to businesses.
Real-Time Collaboration
Team and client collaboration are other benefits of cloud-based solutions. This feature is highly beneficial for companies with a hybrid or remote team.
Environment Friendly
Choosing cloud computing means reducing hardware energy consumption. It is a great way to reduce carbon footprint and leave a positive impact.
Enhanced Security
In recent years, cloud security has improved a lot. Now, all the prominent cloud service providers offer you a high level of security.
Fog Computing vs. Cloud Computing
Data Processing Capacity
Fog computing has comparatively fewer data processing power. Applications that need minimal bandwidth should use this. On the other hand, cloud computing comes with high processing capabilities. Hence, it is suitable for big data analytics and complex modeling.
Latency
Latency refers to the time data takes to travel from device to server/device. In fog computing, the latency is low as the data does not have to travel much away from the device. However, cloud computing experiences high latency because the data has to travel to the centralized server.
Responsiveness
Fog computing depends largely upon local hardware. Its response time will vary due to bandwidth limitations and latency. In cloud computing, end-users experience a quick response time with the help of dedicated data centers.
Security
Since fog computing uses localized or distributed networks, it is highly secure. Cloud computing also provides high security with data encryption and other methods. But at the same time, it is more prone to cyber-attacks.
Data Center Location
Fog computing can be geographically distributed, but usually, it is more localized and may only operate from one geographic location. Contrarily, cloud computing is geo-distributed as it uses a network of cloud servers located in multiple geographical regions.
Communication Mode
Fog computing needs different wireless (WLAN, WiFi, 3G, 4G) or wired communication. However, cloud computing uses an IP network to operate.
Core Network Dependency
With fog computing, you see a decentralized approach that utilizes the edge of the network for data storage and processing. These include individual devices or sensors. On the flip side, cloud computing relies on a strong and dependable core network. If the network quality is low, data can become corrupted or lost.
Server Nodes
Due to its nature, fog computing needs to utilize a large number of server nodes to process the data. But, cloud computing uses fewer server nodes.
Fog Computing Use Cases in IoT
#1. Video Surveillance
The most prominent use of fog computing in IoT is video surveillance which is used in shopping malls, streets, and other large public areas. The nodes can instantly detect anomalies in the crowd and alert authorities automatically in case of any sign of violence.
#2. Smart Homes
Using fog computing, you can create a personalized alarm system at your home. It helps you automate certain actions from your smart home system, such as thermostats, sprinklers, intercoms, and alarms.
#3. Healthcare
The healthcare industry is always in need of technologies to detect and address emergencies in real-time. Fog computing allows wearables, blood glucose monitors, and other health devices to find out about critical situations, like a stroke, in advance.
#4. Traffic Light System
A smart traffic light system can interact locally using fog computing. It can detect the number of people and vehicles on the road and measure the speed of vehicles to display warning signals.
#5. Gaming 🎮
Gamers can also use fog systems to play online games. It uses local game centers to ensure low latency and a better experience during multiplayer online gaming.
Cloud Computing Use Cases in IoT
#1. Healthcare 🩺
Cloud systems can make data available to all the stakeholders so that they can quickly come up with diagnoses and decisions. With the right technology, medical services can be moved to the home of the patient.
#2. Surveillance
Cloud systems play a key role in analyzing video streams and ensuring security. It can analyze the videos and send alerts to the server about any suspicious person or activity.
#3. Logistics
Cloud computing can also make the logistics system smart. It can fetch and share the user demand in real-time with the inventory so that it can be fulfilled immediately.
#4. Smart City
Smart cities need cloud computing to offer an interactive and effective experience to their residents. It can contribute to public safety, tourism, transportation, and urban consumption.
#5. Environment Monitoring
You can use cloud systems in sensitive zones like oil rigs and industrial facilities. It can share real-time information with the stakeholders about water quality, pollution, air quality, smoke, and soil humidity.
#6. Power Distribution
Energy distribution and management is another sector where you can utilize cloud computing. Its sense nodes can collect data and analyze it for intelligent resource utilization.
Can Fog and Cloud Computing Complement Each Other? 🤝
Cloud computing offers you the efficiency needed for modern-day applications. Moreover, it facilitates real-time communication for personal and business purposes. However, it fails to address challenges such as high bandwidth and low latency. On the other hand, fog computing has answers to these issues. Nevertheless, it has its own set of limitations: local backup, redundancy, and communication are usually restricted to devices within a limited service area. The good thing for the users is fog and cloud computing can complement each other. By blending these two solutions, you can create new communication and experiences. For example, imagine having a connected vehicle network. Cars can transmit road condition data through fog computing to share directly with nearby drivers about potential hazards. At the same time, vehicles can transfer data to a central cloud server through WAN to alert other drivers who might want to take any particular route to reach their destination. While these two services can complement each other, none of it is replaceable by another one. Using fog and cloud computing, one can optimize the connected devices further in terms of data collection, storage, and processing.
Concluding Thoughts
Here, we covered the basics of fog computing and cloud computing; and how these two can be implemented in IoT. After going through the article thoroughly, you can easily tell the difference between fog and cloud computing. Implementing both models together is also feasible. You can also check out the article on utility computing.
