The Edge Computing is one of the technologies that will define and revolutionize the way humans and devices connect to the internet. It will impact industries and sectors such as connected vehicles, video games, Industry 4.0, artificial intelligence, and machine learning. In other words, it will revolutionize and transform technologies like cloud computing and the Internet of Things (IoT). Keep reading to learn more about this technology.
What is Edge Computing?
Edge computing is a type of computing that happens at or near the physical location of the user or data source. This allows users to get faster and more reliable services and enables companies to take advantage of the flexibility of hybrid cloud computing. With edge computing, companies can use and distribute a common set of resources across many locations.
Components of an Edge Computing Network
- Company or Provider's Core System: These are the traditional levels that are not at the edge of the network. They belong to public cloud providers, telecommunications service providers, or large companies and are operated by them.
- Service Provider Edge: These levels are found between main or regional data centers and the final segment of the network. Typically, they belong to telecommunications companies or Internet service providers who also manage them. From here, the provider delivers services to multiple customers.
- End-User Facility Edge: These are the final segments of edge computing that may include enterprise edge (e.g., a retail store, factory, train) or consumer edge (e.g., a home, car).
- Device Edge: Independent systems (not clustered) that directly connect sensors or actuators through non-Internet protocols. This is the farthest edge of the network.
Why Use Edge Computing?
The explosive growth and increasing computing power of IoT devices are generating unprecedented volumes of data. And these data volumes will continue to grow as 5G networks increase the number of connected mobile devices.
Previously, the goal of cloud computing and AI was to automate and accelerate innovation by extracting actionable insights from data. However, the unprecedented scale and complexity of data generated by connected devices have outgrown the capacity of network infrastructure.
Sending all the data generated by devices to a centralized data center or the cloud causes bandwidth and latency issues. Edge computing offers a more efficient alternative: data is processed and analyzed closer to where it is created.
Since the data doesn’t have to travel through a network to a cloud or data center for processing, latency is significantly reduced. Edge computing — and mobile edge computing in 5G networks — allows for faster and more comprehensive data analysis. This creates an opportunity for more detailed insights, faster response times, and improved customer experiences.
How is Edge Computing Used?
Edge computing is a strategy that extends a uniform environment from the main data center to physical locations closer to users and data sources. Just like a hybrid cloud strategy allows businesses to run the same workloads in both their own data centers and a public cloud infrastructure (e.g., Amazon Web Services, Microsoft Azure, or Google Cloud), an edge computing strategy extends the cloud environment to many more locations.
Today, edge computing is used in many sectors such as telecommunications, manufacturing, transportation, and utilities, among others. The reasons for implementing this technology vary just as much as the companies that use it.
There are more and more IoT devices being used regularly both in business/industrial settings and in homes. New 5G mobile networks facilitate the deployment of these interconnected elements, allowing for mass access to data networks so they can exchange information with each other and data centers.
Edge computing is the ideal complement for these two technologies by enabling the execution of processes and data management directly on IoT devices without the constant need to send data to the cloud.
For example, with the use of containers, applications can be packaged to run on IoT hardware devices and operate at the edge, without experiencing delays from remote communication with a cloud server.
What Are the Advantages of Edge Computing?
- Faster, More Stable, and Lower-Cost Services: With edge computing, services can be delivered faster, more stably, and at a lower cost. For users, this means a faster and more consistent experience. For businesses and service providers, it translates into low-latency, high-availability applications with constant monitoring.
- Reduced Network Costs: Edge computing can decrease network costs, avoid bandwidth restrictions, and reduce transmission delays. It also helps limit service errors and better control the transfer of sensitive data. Load times are reduced, and online services implemented closer to users enable both dynamic and static caching functions.
- Better Control of Data: With edge computing, businesses can manage their data more effectively by not having to send much of it through the network. An example is facial recognition systems, where user data doesn't need to travel across the network to remote servers but stays on the device itself.
Additional Benefits of Edge Computing
- Big Data Aggregation and Analysis at the Edge: Another benefit of edge computing is the ability to aggregate and analyze big data on-site, allowing for near-instant decision-making. Edge computing further reduces the risk of exposing confidential data by keeping computing power nearby. This also allows businesses to implement security practices or comply with regulatory policies.
- Flexibility and Cost Savings for Business Clients: Business clients benefit from the flexibility and cost savings associated with edge computing. By keeping computing power close, regional sites can continue to operate independently of the central site, even if the latter goes down. Additionally, by maintaining processing power closer to its source, the cost of bandwidth required to move data between regional and central sites is significantly reduced.
- Always-On, Low-Latency Operation: Edge computing is always on, with very low latency due to reduced network activity, and it avoids bandwidth limitations. The characteristics of edge computing allow for immediate action, overcoming the limitations of transferring data over the internet (sending data to a remote server for processing and then back).
- Cloud Computing Cost Reduction: By relieving much of the load on cloud servers, edge computing helps reduce cloud computing costs. The cost of providing data storage services and immediate transmission is significantly reduced.
- Uniformity in Operations and Application Development: An edge computing platform brings uniformity to operations and application development. Unlike data centers, it must support interoperability across a wider range of hardware and software environments. An effective edge computing strategy also allows products from multiple vendors to work together in an open ecosystem.
Staying informed about each technological advancement that can help your company evolve is always beneficial. Are you ready for the digital revolution?
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