Edge and Cloud Computing
In manufacturing, edge computing refers to the use of distributed computing power and data storage closer to the source of the data, rather than relying on a centralized network or cloud. Edge computing allows for faster processing of data and can be used to analyze and act on data in real-time, enabling manufacturers to make more timely and informed decisions. Cloud computing allows manufacturers to store and access data from any location, using a range of devices such as laptops, tablets and smartphones. This can help manufacturers to improve data management, collaboration and communications, and make data-driven decisions to optimize operations and improve efficiency.
Edge and Cloud Computing Articles
Top 5 benefits Edge Computing delivers for next-generation control
Edge computing provides local compute capability for shop-floor equipment or remote assets, creates an essential bridge between real-time data acquisition from mission-critical processes to the control center, cloud, or unified operations centers. Forward-thinking organizations employ edge computing to run human-machine interface (HMI), supervisory control and data acquisitions (SCADA) and distributed control system (DCS) applications with maximum reliability, enable advanced solutions such as artificial intelligence/machine learning (AI/ML). Edge computing also meets the requirements of converged operational technology/information technology (OT/IT) implementations.
Join industry expert Craig Resnick, vice president, ARC Advisory Group, as he shares the top five reasons edge computing is essential for next-generation control. The session also provides crucial tips on how to identify key considerations for selecting the right edge platform for the organization.
This webcast explains the top five ways edge computing:
- Supports better decision making by speeding processing of your real-time data
- Enables a more agile and responsive monitoring and control system
- Reduces overhead and total cost of ownership (TCO)
- Enables next-generation control solutions like AI and ML
- Provides an easier path to edge automation
Edge and Cloud Computing FAQ
What is the difference between edge and cloud computing?
Edge computing refers to processing data close to the source of data, often at or near the edge of a network. Cloud computing involves processing and storage of data on remote servers accessed through the internet. Edge computing aims to reduce the amount of data transferred to the cloud and reduce latency, while cloud computing offers scalability and centralized data management.
Can edge and cloud computing co-exist?
Yes, edge and cloud computing can co-exist. Edge computing often is used to preprocess data before sending it to the cloud for storage and further analysis. The cloud can provide additional processing power and storage resources for complex operations, while the edge can provide real-time data processing capabilities. Combining edge and cloud computing can provide the benefits of both technologies and create a more efficient and flexible computing infrastructure.
What is the relationship between edge and cloud computing?
Edge and cloud computing have a complementary relationship, with each offering unique capabilities and advantages. Edge computing is often used for real-time data processing and decision making at the edge of a network, while cloud computing is used for large-scale data storage and processing. The data processed at the edge can be sent to the cloud for further analysis, and the results can be sent back to the edge for immediate use. This relationship allows for a more efficient and flexible computing infrastructure, as the cloud can provide additional processing power and storage resources as needed, while the edge can provide low-latency data processing capabilities.
What are the five benefits of edge computing?
- Reduced latency: Edge computing processes data closer to the source, reducing the time it takes for data to be transmitted to the cloud and back.
- Improved reliability: Edge computing can mitigate the risk of data loss or delays that may occur due to network disruptions by processing data locally.
- Increased security: Sensitive data can be processed and stored at the edge, reducing the risk of cyberattacks or data breaches.
- Better scalability: Edge computing allows for processing at multiple locations, reducing the strain on central servers and making it easier to scale operations as needed.
- Cost-effectiveness: By processing data locally, organizations can reduce the amount of data they need to send to the cloud, potentially reducing costs associated with cloud storage and bandwidth.
Some FAQ content was compiled with the assistance of ChatGPT. Due to the limitations of AI tools, all content was edited and reviewed by our content team.