In our previous volumes on edge computing (one, two, three and four), we discovered how edge computing relates to the Internet of Things (IoT), how it can help to minimize infrastructure demands in a data center and how mobile edge computing can help in achieving greater efficiencies. In this article, we’ll explore the topic of privacy and security in relation to edge computing.
Edge computing is driven by mobile computing and the increasing number of networked devices in the Internet of Things (IoT). IoT is the inter-networking of physical devices, vehicles (also referred to as “connected devices” and “smart devices”), buildings and other items embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data.
The biggest advantage of edge computing is that it drastically improves response time by processing data right at the source, all while conserving network resources. Processing data locally means that there is an increase in efficiency as regards a decision made for a call to action and less movement of data since only the valuable information is being sent back to the cloud, and not the excess. By keeping this data in one environment, there is less of a chance for security issues while data is being transferred.
Edge computing can also provide real-time response services that enable IoT systems to respond to security issues without disrupting services. This is critical in edge applications where downtime could be detrimental. For example, if a power generator were compromised, shutting it down to fix the problem could be an issue. Edge computing can help the issue get resolved by determining in real-time if the generator is at fault or not without having to take the generator down, avoiding power outages or disruptions in service.
In addition to optimized privacy and security, many technology experts expect edge computing to be mainstream in the next five-to-10 years due to the following benefits:
- Real-time data analysis at the local device level, not in a distant data center or cloud.
- Lower operating costs due to smaller data management expenses of local devices.
- Reduced network traffic from local devices via a network to a data center or cloud, decreasing network bottlenecks.
- Improved application performance as apps that don’t tolerate latency can achieve lower inactivity levels on the edge, as opposed to a distant cloud.
For more information on optimizing privacy and security through edge computing, please contact our team today.