Similar to the migration from on-premise servers to cloud computing, companies are investing in the next technological progression—edge computing. As the name suggests, edge computing brings the computational infrastructure closer to the data source (i.e., the edge of a network), where it enables faster and more reliable services, as well as improved flexibility.
This network architecture helps to overcome some of the issues with cloud computing because nearby devices are used as servers to improve response times and reduce latency. Organizations from all industries are looking closely at edge computing as a component of their digital transformation strategies.
What Is Edge Computing?
In simple terms, edge computing brings the computational infrastructure closer to the data source, which can provide faster access to and analysis of that data. The proximity of the data source and the data computation addresses some of the limitations of cloud computing by improving bandwidth, reducing latency, and lowering costs.
Edge computing is particularly useful in situations with limited bandwidth or unreliable networks because it doesn’t require an Internet connection. It’s also helpful with artificial intelligence or machine learning applications where a great deal of real-time data is produced and needs to be analyzed quickly.
Additionally, multi-access edge computing refers to the edge of any network, while mobile edge computing refers to the edge of only the mobile network.
How Does Edge Computing Support the Internet of Things (IoT)
The objective of edge computing is that computing should happen in the proximity of data sources. As a result, edge computing is particularly beneficial for supporting the Internet of Things (IoT), sometimes called machine-to-machine (M2M) communications in the industrial world. Because the IoT generates a lot of data in a short time, edge computing offers improvements over other cloud computing infrastructures.
The IoT gathers information directly from multiple devices, which can be almost anything with a sensor—including computers, vehicles, smartphones, appliances, building automation systems, and production equipment. Typically cloud computing is not efficient enough to handle the growing quantity of data generated by all those devices. Edge computing brings computation closer to IoT devices, improving response time, reducing latency, improving bandwidth, and lowering costs.
What are the Benefits of Edge Computing?
Edge computing extends cloud-based computing to geographically distributed locations, bringing computation closer to the devices that produce data. That offers benefits such as improvements in…
- Bandwidth
- Power consumption
- Response time
- Security
- Reliability
- Performance
- Latency
- Scalability
- Costs
What are the Challenges of Edge Computing?
Unlike cloud computing, where servers are located elsewhere, edge computing involves physical devices located in close locations. As a result, it requires professional IT services to set up and monitor the network.
Like any technological innovation, challenges must be addressed before implementation. These challenges include…
- Stable power supply
- Hardware location
- Maintenance
- Security
Edge computing is still a nascent technology, although the market is expected to expand rapidly. Many companies are looking at edge computing as part of their long-term digital transformation strategies because of its ability to streamline business processes. The appeal is the ability to extend conventional cloud computing with a distributed infrastructure where applications are closer to the sources where the data is captured.
Contact InApp for more information about edge computing, and how it can help your organization.
