Edge Computing, a fuzzy term is a networking technology that mainly focuses on bringing core computing as close to the source of data in order to reduce the latency and bandwidth. In similar terms, edge means running fewer processes in the local places, such as on a user’s computer, an IoT device, or an edge server.
The network “On the edge” is geographically close to the device, unlike origin servers and cloud servers, which are very far from the devices they communicate. Also setting up the computing platform to the network’s edge minimizes the amount of long-distance communication that has to happen between a client and server.
It is crucial for modern digital platforms and smart devices to respond in real-time without waiting to hear from a cloud server.
Edge computing plays a very vital role for all the Real-Time technology developments by setting a platform to process and analyze their data at the edge, which makes it possible to do so in real-time.
Edge Computing — A Highline model
Edge computing is the Highline and efficient computing model, as the quantity of digital data that is created day in and day out in the modern cloud platforms practiced has become a point of high attention considering the latency for each data processing cycle across the globally distributed cloud servers.
Edge computing treats the deployed source as a mini datacentre and processes data faster in fractions of seconds. An Edge network helps to process time-sensitive data in remote locations with limited or no connectivity to a centralized location.
The below are the various computing models that are followed currently in the digital industry where the applications are highly centralized via servers located geographically via various means.
- Edge computing: Centralized applications running on the device locally as mini datacenters.
- Cloud computing: Centralized applications running in data centers distributed globally.
- Personal computing: Decentralized applications running locally
Edge Computing — Usecases
Edge computing has its use case implemented into a wide variety of highly applications, products, and services that have transformed the technology world into the world of Artificial Intelligence, Machine learning.
A few possibilities include:
- High and Automatic Security system
- IoT devices
- Automatic Self-driving cars
- More efficient caching
- Medical monitoring devices
- Video conferencing
Benefits of Edge Computing
- Decreased latency
- Decrease in bandwidth use and associated cost
- Decrease in server resources and associated cost
- Added functionality
Drawbacks of Edge Computing
- Increased local hardware
- Increased chance of malicious attacks
- Cost of extra hardware for smart device connectivity