Edge computing is more reliable because it allows data to be processed and stored closer to the source, reducing the need to transmit large amounts of data to a centralized location.

This can result in a number of benefits that improve reliability:

1. Reduced network congestion: By processing data locally, edge computing reduces the amount of data that needs to be transmitted over the network, which can help reduce congestion and improve overall network performance.
2. Improved fault tolerance: Edge computing allows for distributed processing and storage, which can help ensure that data is still accessible even if one or more devices fail.
3. Reduced latency: By processing data locally, edge computing can reduce the amount of time it takes for data to be processed, which can improve the responsiveness of applications and services.
4. Increased availability: Edge computing can provide local processing capabilities even when the network is unavailable, allowing for the continuity of services and reducing the risk of downtime.
5. Better security: Edge computing can provide a more secure environment for data processing, as it allows for more granular security measures, such as device-level authentication, to be implemented and also reduces the risk of data breaches and hacking attempts as the data is not as easily accessible to potential attackers.

By providing these benefits, edge computing can help ensure that applications and services are more reliable and available to users.

The reliability of edge computing will depend on a number of factors, such as the type of devices and gateways used, the software and infrastructure that support it, and the way it’s implemented and maintained. However, it is widely acknowledged that edge computing can improve the reliability of systems by distributing processing and storage closer to the source, reducing network congestion, improving fault tolerance, and increasing availability.

It’s worth noting that edge computing is still a relatively new technology and many organizations are still in the process of exploring how best to implement it.