Understand Edge Computing – From Basics to IoT Applications

Edge computing refers to an architecture that places computing resources close to where data is created on the edge of a network to support smart devices and the Internet of Things (IoT) use cases.

Why is Edge Computing Important?

Edge computing is important because it distributes computing resources in a way that protects centralized servers and networks from becoming overwhelmed. Distributing compute power near where data is created allows systems to scale to support thousands of network endpoints such as sensors. Processing data close to where it is created reduces the volume of traffic that must traverse a network, which results in lower latency and faster data gathering and analysis.

The Rise of Edge Computing

Before the 1980s, computing mainly occurred in centralized data centers, which served networks of dumb terminals. Some minicomputers offered local processing in offices. However, the Personal Computer revolution democratized computing by distributing processing across Local Area Networks to share resources such as shared storage with each other.

Cloud computing quickly replaced private data centers with public data clouds and VPNs using internet connections to browsers on personal computers and tablets. Wi-Fi networks replaced hard-wired LAN connections.

Manufacturing uses multiple sensors to control quality and to adjust machines in real-time to remain within tight tolerances and report issues faster. Here, minicomputers used to play a role. Embedded computers have replaced these.

Automotive systems use sensors and computers to monitor internal functions such as tire pressure and cameras to assess what’s happening around them for safety. The recent worldwide chip shortage highlighted how processor-rich a modern car is and the importance of being able to keep compute and data close to the source for edge devices.

High-value complex machines such as gas and hydro turbines generate enough telemetry using embedded systems to create a digital twin, which the manufacturer can monitor in real time for proactive and preventative maintenance.

Internet of Things (IoT) architectures drive the need for IPv6 to support billions of endpoints such as smart meters, sensors, and security camera feeds. Without local processing, the volume of data these IoT devices generate would quickly overwhelm networks.

Embedded computers and IoT gateways are edge computing devices. They operate within and close to sensor devices that can locally analyze, filter and compress data before it is sent to centralized cloud servers.

Data Storage and Analysis at the Edge

Edge computers are usually low-cost with a small memory footprint. Applications that process sensor data run in a small amount of memory and require zero administration. They are deployed in large numbers, so it is prohibitively expensive to manage individual sensors directly. The most common data storage format is flat files, which are easy to write but hard to use for data analysis.

Actian for Edge Computing

The Actian database is architected for embedded and IoT Edge Computing. The database is superior to flat files as it is more performant and supports local analysis using key-based and SQL access. Having so many connected devices at the edge creates a potential security problem. It uses an AES 256-bit key encryption to protect data at rest and as it is being transmitted.

The Actian database can run in a tiny memory footprint, making it ideal for IoT applications. As processing power increases, as in mobile and IoT Gateway computers, it becomes more feature-rich. One of the most compelling features of the database is its file format, which is the same on an OS like Android and Windows or Linux, eliminating data transformation at the edge.

Actian and the Data Intelligence Platform

Actian Data Intelligence Platform is purpose-built to help organizations unify, manage, and understand their data across hybrid environments. It brings together metadata management, governance, lineage, quality monitoring, and automation in a single platform. This enables teams to see where data comes from, how it’s used, and whether it meets internal and external requirements.

Through its centralized interface, Actian supports real-time insight into data structures and flows, making it easier to apply policies, resolve issues, and collaborate across departments. The platform also helps connect data to business context, enabling teams to use data more effectively and responsibly. Actian’s platform is designed to scale with evolving data ecosystems, supporting consistent, intelligent, and secure data use across the enterprise. Request your personalized demo.