K
Kathleen Martin
Guest
Let’s say that your job is to monitor oil well operations across a small country. You have a device installed at every oil pumpjack, the mechanism that pumps oil out of the ground from an existing well. This device monitors local weather and pump operations. It even automates local processes on the pumpjack.
Collectively, these devices are known as edge computers. They have their own processors, local storage systems, operating systems, and networking interfaces that allow them to communicate with a centralized collection and analysis system. This centralized system uses artificial intelligence and data analytics to determine when human operators need to be dispatched. For instance, the device can determine when a pump motor is about to fail or when oil flow is too high or too low.
The devices also leverage centralized data collection to monitor overall production and provide oversight for all the pumpjacks producing oil. There are 500 devices in this specific edge computing network, one for each remote pumpjack, and all devices communicate back to a centralized system on a public cloud provider.
The first few months of using these edge computing devices to monitor remote and unmanned pumping operations went fine. However, storage systems on the devices soon began to fail due to a known flaw, and network interfaces stopped and had to be reset. Most often, some key sensors used on the pumpjack stopped working. These problems could only be fixed by sending out humans to fix them, thus incurring a cost that defeated the purpose of leveraging these devices to automate pump operations.
To address this problem, remember that we should deal with edge computing like any other compute and storage platform under operational control—do the basics. Back up the data on each edge device, remote to central. Remotely update the operating systems and firmware much like you do on a smartphone. Support application updates that include changes to the data structure. Also, track the configuration, including operating system releases, application updates and patches, and even the software versions running on some of the smart sensors.
Continue reading: https://www.infoworld.com/article/3655641/where-edge-computing-breaks-down-operations.html
Collectively, these devices are known as edge computers. They have their own processors, local storage systems, operating systems, and networking interfaces that allow them to communicate with a centralized collection and analysis system. This centralized system uses artificial intelligence and data analytics to determine when human operators need to be dispatched. For instance, the device can determine when a pump motor is about to fail or when oil flow is too high or too low.
The devices also leverage centralized data collection to monitor overall production and provide oversight for all the pumpjacks producing oil. There are 500 devices in this specific edge computing network, one for each remote pumpjack, and all devices communicate back to a centralized system on a public cloud provider.
The first few months of using these edge computing devices to monitor remote and unmanned pumping operations went fine. However, storage systems on the devices soon began to fail due to a known flaw, and network interfaces stopped and had to be reset. Most often, some key sensors used on the pumpjack stopped working. These problems could only be fixed by sending out humans to fix them, thus incurring a cost that defeated the purpose of leveraging these devices to automate pump operations.
To address this problem, remember that we should deal with edge computing like any other compute and storage platform under operational control—do the basics. Back up the data on each edge device, remote to central. Remotely update the operating systems and firmware much like you do on a smartphone. Support application updates that include changes to the data structure. Also, track the configuration, including operating system releases, application updates and patches, and even the software versions running on some of the smart sensors.
Continue reading: https://www.infoworld.com/article/3655641/where-edge-computing-breaks-down-operations.html
