researchHQ’s Key Takeaways:
- Edge computing offers increased flexibility and enhanced efficiency through real-time processing of data at the edge of an organisation’s network.
- Despite edge computing’s distributed architecture, edge gateways quickly analyse data before sending the processed data to a central cloud system.
- Cloud & Edge Computing can provide ancillary benefits to one another, covering each other’s shortcomings to become more efficient and responsive.
Does edge computing spell the end of cloud computing? Should we use them both? How can we be sure we’re using the right approach? We cover the ‘edge computing vs. cloud computing’ debate in this article to help you clear things out.
Edge Computing Will Decrease Latency, Enhancing Efficiency for Real-Time Analytics Apps
The rise of interest for edge computing has followed the rise of the Internet of Things (IoT). Webopedia refers to it as the ever-growing network of physical objects that feature an IP address for internet connectivity, and the communication that occurs between these objects and other Internet-enabled devices and systems.
‘Ever growing’ is a well-chosen term indeed, especially as Cisco predicts that 50 billion devices will be connected to the Internet of Things (IoT) by 2020. We can just imagine the level of network bandwidth usage this is going to generate over the next years if we keep up with the cloud computing approach. Real-time processing needs infrastructure at the edge or close to the data source.
Luckily, edge nodes are ideal to solve issues such as network bandwidth overuse and lack of flexibility that are often caused by large-scale, centralized cloud infrastructures. So, when it comes to comparing edge computing vs. cloud computing, the key benefit of an edge computing approach is that it offers much lower latency for client applications. ‘First-step’ computing can be done at the ‘edge’ of a system, reducing latency dramatically and ensuring high uptime and reliability. In turn, this makes IoT applications more efficient.
Edge Computing Will Provide the Local Processing Power That Cloud Computing Can’t
Edge computing is, by design, a distributed architecture rather than a centralized one. It responds to the processing need for one application or set of applications, connecting smart devices in one regional area to processing power locally.
In other words, edge computing tends to have an overall lower processing load, compared to centralized cloud computing architectures. However, this is not a bad thing – because edge nodes are used to:
Quickly analyze data they receive from client devices
Send back the results of the computation to these devices
Also, because they act as ‘gateways’, they’ll send the processed information to a central cloud system for long-term storage or further treatment. Thus, the name ‘edge gateways’.
