Difference between Cloud, Fog and Edge Computing in IoT

Jan 26, 2020

Digiteum Team

cloud, fog and edge computing

IoT

Difference between Cloud, Fog and Edge Computing in IoT

We’ve heard a lot about cloud computing as the most prominent form of IoT data management. Along with cloud computing, fog and edge computing are becoming popular as well. Let’s compare these three forms of data technologies, examine their differences and benefits.

IoT cloud Edge Fog

Table of Contents

  1. Cloud, Edge and Fog Computing in IoT Environment
  2. Difference Between Fog And Edge Computing
  3. How do fog and edge computing work?
  4. Advantages of Fog Computing and Edge Computing
  5. The Role Of Cloud Computing in IoT
  6. What is the Future with IoT and Cloud Computing
  7. IoT Computing Solutions With Digiteum

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Cloud Computing in IoT Environment

Cloud computing is the standard of IoT data storage right now. It’s the form of computing where data is stored on multiple servers and can be accessed online from any device. Instead of saving information to the local hard drive on a single computer, users store it on third-party online servers.

To access data, a user needs to enter an account associated with the cloud service. The data undergoes end-to-end encryption, so even service providers have no access to the user’s contents. For the Internet of Things, this means securely storing and managing a lot of data and having immediate access to it from multiple devices, anytime, anywhere.

Difference Between Fog And Edge Computing

These computing technologies differ by their design and purpose but often complement each other. Let’s take a look at edge computing vs fog computing and analyze their purposes and differences.

Fog Computing

The term fog computing was coined by Cisco, and it defines a mix of a traditional centralized data storage system and Cloud. Computing is performed at local networks, although servers themselves are decentralized. The data, therefore, can be accessed offline because some portions of it are stored locally as well. This is the key distinction between fog computing vs cloud computing, where all the intelligence and computing are performed on remote servers.

Edge Computing

Edge computing processes data away from centralized storage, keeping information on the local parts of the network — edge devices. When the data is sent to the edge device, it can be processed directly on it, without being sent to the centralized cloud.

How do fog and edge computing work?

Fog computing is useful when the Internet connection isn’t always stable. For instance, on connected trains the fog system can pull up locally stored data on areas where the Internet connection can’t be maintained.

How is data processed by fog computing?

  • Urgent requests are sent directly to the fog and processed locally in the network;
  • Less sensitive data is transferred to the cloud’s main data centers where it’s stored and analyzed;
  • Under normal conditions, the majority of data goes to the cloud, local storages are used in scenarios where saving bandwidth is a priority.

Fog computing allows to implement data processing at the local networks, especially if it has to be processed in real time. This is what makes this storage form incredibly stable under stressful conditions, especially when comparing cloud vs fog computing.

Edge computing is the least vulnerable form of decentralized storage. On the cloud, data is distributed to dozens of servers, whereas edge computing uses hundreds, possibly thousands of local nodes. Each device can act as a server in the edge network. To break into, hackers would need access to thousands of destributed devices, which is practically impossible.

IoT connectivity technologies

Advantages of fog computing and edge computing

Edge and fog computing are less known than cloud but have a lot to offer to businesses and IoT companies in particular. These networks solve many issues that can’t be solved by IoT cloud computing services and adapt the decentralized data storage to particular needs. Let’s examine their benefits individually before comparing these systems side by side.

Benefits of fog computing

  • Low latency. The fog network can process large volumes of data with little-to-no delay. Because a lot of data is stored locally, the computing is performed faster.
  • Better data control. In cloud computing, third-party servers are fully disconnected from local networks, leaving little to no control over data. In fog computing, users can manage a lot of information locally and rely on their security measures.
  • A flexible storage system. Fog computing doesn’t require constant online access. The data can be stored locally or pulled up from local drives — such storage combines online and offline access.
  • Connecting centralized and decentralized storage. Fog computing builds a bridge between local drives and third-party cloud services, allowing a smooth transition to fully decentralized data storage.

Many companies focus on edge computing on their way to decentralization, whereas others adopt fog computing as a main data storage system due to its high speed and increased availability.

Benefits of edge computing

  • No delays in data processing. The data stays on the “edges” of the IoT network and can be acted on immediately.
  • Real-time data analysis. Works great when large amounts of data have to be processed and immediately.
  • Low network traffic. The data is first processed locally, and only then sent to the main storage.
  • Reduced operating costs. Data management takes less time and computing power because the operation has a single destination, instead of circling from the center to local drives.

IoT edge computing is an optimal solution for small immediate operations that have to be processed with millisecond rates. When many small operations are happening simultaneously, performing them locally is faster and cheaper.

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Role of Internet of Things and cloud computing

Cloud computing and IoT are often talked about in conjunction because the two technologies support each other. Internet of Things relies on different Cloud services store and analyze IoT device data and metrics, enable automation, etc.

Let’s see how cloud computing and IoT bring benefits to business and end-users, and why it’s advantageous to use them together.

  • Increased scalability. IoT systems produce and exchange a lot of data and require a lot of storage space to seamlessly function. Internet of Things services on Cloud platforms like Microsoft Azure IoT Suite, Google Cloud’s IoT service, and IBM’s IoT platform provide access to powerful cloud services able to handle all this IoT data.
  • Improved safety. IoT services should rely on safe data storage able to prevent hackers from trying to access and jeopardize the system. Decentralized storage represents one of the ways to secure sensitive resources.
  • Enable IoT. Decentralized data storage corresponds with the main IoT needs, such as accessibility, safety, mobility, and scalability. Cloud services process massive amounts of data and quickly distribute the information among multiple servers, where it can be later accessed by a connected device anytime.

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The future with IoT, edge, fog and cloud computing?

Cloud technology already brings multiple benefits to the Internet of Things, but progress doesn’t stop here. Right now, cloud, fog and edge technologies provide irreplaceable solutions to many Internet of Things challenges. Let’s take a look at some future possibilities for Internet of Things and different computing technologies.

New deployment options

IoT sector is rapidly growing, and we are likely heading into a future where every device is connected. With smart homes, cars, equipment, and everything else, vast masses of data are generated every second. Devices will continue to require increases in computer power, and cloud computing offers decentralized storage solutions for faster and cheaper deployments. Developers only have to connect their systems to IoT cloud platform existing infrastructure to benefit from third-party computing power.

Tesla autopilot big data

Smart analytics

Internet of Things systems produce a lot of data. Developers and businesses can use it to know their users better. Cloud services provide a safe environment where this data could be analyzed, managed, and stored. Many services are already equipped with AI capabilities, including machine learning algorithms that model insights from data and enable automation.

Better security

A security breach in IoT networks could mean compromising entire businesses and industries, affecting millions of connected devices and people who use them. Cloud storages are more difficult to target because of their remote position and security practices. In the future, devices can use previously collected data to detect vulnerabilities before they even show.

Inter-device interactions

The cloud improves communication between devices and applications, quickly sending data between data centers and local nodes. Fog and edge computing can be useful for offline communication and micro-operations, reducing operation costs and increasing speed.

IoT computing solutions at Digiteum

At Digiteum, the Internet of Things is our prominent field of expertise. We’ve developed many Internet of Things B2B and B2C systems, and cloud computing is a must-implement technology for most of them.

When working on a project, we estimate how much data a product is likely to process at any given moment and choose computing and data management solutions accordingly. Take a look at our projects and drop us a line. If you have a project in mind, we are ready to bring our Internet of Things expertise to help you implement it.

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