Edge Computing: The Next Frontier in Technology
What is edge computing?
Edge computing is an emerging computing paradigm which refers to a range of networks and devices at or near the user. Edge is about processing data closer to where it’s being generated, enabling processing at greater speeds and volumes, leading to greater action-led results in real time.
Edge devices: We already use devices that do edge computing every day—like smart speakers, watches and phones – devices which are locally collecting and processing data while touching the physical world. Internet of Things (IoT) devices, systems, robots, vehicles and sensors can all be edge devices—if they compute locally and talk to the cloud.
Advantages of Edge Computing:
- Faster Decision-Making: Processing data where it’s generated, speeds up decision-making which is essential for applications that need quick responses, like in healthcare, finance, and manufacturing.
- Scalability: Edge computing helps distribute processing across multiple locations, easing the strain on central data centers and improving the ability to manage large volumes of data from IoT devices.
- Low Bandwidth Usage: Edge computing enables IoT apps to use less bandwidth, allowing them to function normally even when connectivity is limited.
Disadvantages of Edge Computing
- Network Susceptibility: The networked architecture of edge computing increases known attacks. Such a system is susceptible to security flaws and malware infiltration.
- Balancing Bandwidth: As more data is secured at the edge, more computers are required. As a result, the bandwidth must be increased. Therefore, the implementation of edge computing necessitates the balancing of network bandwidth.
- Technical Issues: Since these Data Centers lack the comprehensive infrastructure of a typical Core Data Center, they must work around some technical challenges.
Edge Computing Vs. Cloud Computing:
Edge Computing | Cloud Computing | |
Definition | Edge Computing means dealing with data right where it’s created—like on-site at a factory or in a car. This speeds up how quickly you can get responses and avoids the delays that come from sending data long distances. | Cloud Computing involves keeping your data on servers that are far away. While this lets you get to your files from anywhere, it also means you have less say over your data once it’s stored on someone else’s servers. |
Data Distribution | Edge computing spreads data across multiple locations. | Cloud computing keeps all data in one central spot. |
Focus | Edge computing is about quick, real-time data handling and communication between devices. | Cloud computing is about managing and analyzing large amounts of data at once. |
Data Processing | In Edge Computing, the data processing happens at the edge of the network. | In Cloud Computing, data processing happens in the cloud. |
Storage Involved | Edge computing involves local storage. | Cloud computing involves remote storage. |
Use Cases | Edge computing is better suited for devices that need fast connections and low latency (such as drones). | Cloud computing lends itself more naturally to applications where large amounts of data need to be processed at once (such as image recognition). |
Cost Effectiveness | Edge computing is less cost-effective. | Cloud computing is more cost-effective because it centralizes resources in a single location. |
Which industries use edge computing?
Manufacturing
The rise of Internet of Things (IoT) devices like sensors and gateways has made edge computing a popular choice. These systems allow factories to process data locally, which speeds up decision-making and improves efficiency on the production line.
Autonomous vehicles
Autonomous vehicles such as self-driving cars, edge computing is essential. Self-driving cars are packed with IoT sensors that collect huge amounts of data every second. To make quick decisions, like dodging obstacles, they need to process this data instantly. Relying on a remote server would be too slow, so real-time processing is crucial to ensure safety.
Energy
Energy companies use edge computing to collect and store data on oil rigs, gas fields, wind turbines, and solar farms.
Healthcare
Edge devices monitor critical patient functions such as temperature and blood sugar levels. Edge computing allows the healthcare sector to store this patient data locally and improve privacy protection.
Edge computing companies
Summary
The purpose of edge computing is to bring your applications closer to where the data is created and action must happen. When you do this, you can achieve much faster response times (very low latency from when an event happens until a response occurs). With edge computing, you can also analyze more data at higher resolutions and frequencies.