The term Edge Computing refers to having computing infrastructure closer to the source of data. It is the distributed framework where data is processed as close to the originating data source as possible. This infrastructure requires effective use of resources that may not be continuously connected to a network such as laptops, smartphones, tablets, and sensors.
With the increasing demand for real-time processing and reduced latency, edge computing is set to dominate software architecture trends. In 2024, architectures will be designed to leverage edge computing capabilities, enabling applications to process data closer to the source. This approach enhances responsiveness, particularly crucial for applications in IoT and critical systems. The integration of edge computing with 5G/6G infrastructure is expected to enhance its capabilities, reducing complexity, and strengthening cybersecurity defenses.
Following are some promising Use Cases for Edge Computing:
- Privacy: Avoid sending all raw data to be stored and processed on cloud servers.
- Real-time responsiveness: Sometimes the reaction time can be a critical factor.
- Reliability: The system is capable of working even when disconnected from cloud servers. Removes a single point of failure.
According to a study, an autonomous car will generate 40 terabytes of data for every eight hours of driving. Now with that amount of data, the time of transmission will go substantially up. In the cases of self-driving cars, real-time or quick decisions are an essential need. Here edge computing infrastructure will come to the rescue. These autonomous driving cars need to make decisions quickly, requiring computer processing on board the vehicle.
Another example is the growth of unmanned drones or quadcopters. Onboard decisions are required to take corrective action. These machines need to be intelligent enough to take like course correction, target identification, and destination verification.
Edge Computing aims to minimize latency by bringing the public cloud capabilities to the edge. According to Grand View research, the global edge computing market was valued at USD 11.24 billion in 2022 and is expected to expand at a compound annual growth rate (CAGR) of 37.9% from 2023 to 2030.
Data Transmission is expensive. By bringing computer processing closer to the origin of data, latency is reduced, and the customers/end users have a better experience. Some of the evolving use cases of Edge Computing are Augmented Reality (AR), Virtual Reality (VR), and the Internet of Things.
While edge computing presents numerous opportunities, it also faces challenges, including security risks and the need for specialized infrastructure. Addressing these challenges opens avenues for innovation in cybersecurity and infrastructure development.
Edge Computing Use Case Examples
| Use Case | Brief Description |
| Autonomous Vehicles | Edge computing enables autonomous platooning of truck convoys, potentially eliminating the need for drivers in all trucks except the front one. |
| Remote Monitoring of Oil and Gas Assets | Brings the processing and storage of data closer to the equipment, allowing for real-time health monitoring and analytics. |
| Predictive Maintenance | Brings processing and storage of data closer to the equipment, allowing for real-time health monitoring and analytics. |
| In-Hospital Patient Monitoring | Edge computing on-site provides data privacy, real-time notifications to practitioners, and comprehensive patient dashboards. |
| Traffic Management | Edge computing allows effective city traffic management, optimizing bus frequency, lane usage, and future autonomous car flows. |
| Smart Homes | Bringing processing and storage closer to the smart home can improve the performance and security of smart home IoT devices. |
Author: Shakil Ahmed