- Health IT is advancing, but there’s a missing link between what IT innovators imagine for the future and what their infrastructure is capable of supporting, according to the latest OpenFog Consortium report. Healthcare fog computing can offer healthcare organizations a new way to support their IT solutions as they continue their digital transformations.
Fog computing is a, “system-level horizontal architecture that disputes resources and services of computing, storage, control, and networking anywhere along the continuum from cloud to things,” according to OpenFog.
“It’s more than an interesting approach to today’s data-driven world, it’s a necessary one,” said OpenFog Co-founder and chairman, Helder Antunes said in a statement. “At OpenFog, we have classified the advantages of fog computing as SCALE: Security, Cognition, Agility, Latency and Efficiency. Fog offers all this, and more, through its flexible, distributed architecture.”
This distributed architecture allows computing analytics and decision-making to be done near the data source which is especially efficient for organizations using the Internet of Things (IoT). The report says that fog computing will provide these services with containerization, virtualization, orchestration, manageability, and efficiency.
Fog can also help healthcare organizations solve interoperability issues with the IEEE 1934 standard, which addresses the need for end-to-end interoperable solution for the things-to-cloud architecture used by fog computing.
Open standards for fog computing are critical as IT systems become more complex with cloud and IoT solutions.
“The benefits of collaboration will enable an open, interoperable architecture for fog computing to extend the mobile edge with a physical and logical multi-layer network hierarchy,” said john W. Koon of Tech Idea Research. “These functions are performed by the fog node part of the architecture. Operators only need to connect to the fog nodes, resulting in interoperability across operators.”
Fog computing is the layer between the devices at the edge of the network and the cloud. Fog computing bridges the gap between the cloud and the things at the very edge, along with all the technologies in between.
The horizontal architecture distributes resources and services puts decentralized decision-making power close to the source of the data and can continuously operate even with unreliable network connectivity.
The OpenFog Consortium has built the OpenFog Reference Architecture (OpenFog RA) to give organizations across all industries, including healthcare the ability to develop their fog computing architecture based on a laid-out framework.
“The OpenFog RA RA) is a medium- to high-level view of system architectures for fog nodes and networks. It is the result of a broad collaborative effort of its independently run open membership ecosystem of industry, technology and university/research leaders,” the report explained. “It was created to help business leaders, software developers, silicon architects and system designers create and maintain the hardware, software and system elements necessary for fog computing. It enables fog-cloud and fog-fog interfaces.”
This architecture framework is built upon the previously mentioned IEEE 1934 standard to help ensure consistency throughout.
This year at Fog World Congress, participants across major technology vendors and organizations determined the transformative fog computing trends organizations should keep an eye on over the coming year.
The top trends included 5G and artificial intelligence.
5G offers speeds much faster than he 4G LTE most IoT devices are currently connecting with. While it’s not yet available, fog computing can eventually take advantage of the wider 5G bandwidth and act as a platform for 5G applications that require near real time communication. By running theses applications through a fog layer, even more latency is eliminated because the data doesn’t need to be communicated from the edge, all the way to the cloud.
Processing data close to the source is will also allow organizations to better leverage artificial intelligence. One specific use case of using AI with fog computing is cleaning up “dirty data.”
“Cleaning up dirty data can entail everything from eliminating duplicate data to filling in missing data,” said the report. “It can involve even more challenging preprocessing requirements, such as converting different formats into a common format or language. Fog computing can provide preprocessing closer to the source of the data, to help ensure that cleaner data is forwarded to the cloud for deeper analytics.”
Healthcare organizations are continuing to adopt digital tools to be more innovative, increase workflow and improve patient care. As a result, digital tools are being added which makes a centralized approach more difficult to justify.
As more connections are added from IoT and connected medical devices, considering a decentralized architecture for device to connect to the network can help organizations reduce bandwidth restrictions and create room for the continued addition of more connected devices.
The added layer of fog computing can help distribute the weight of data sets, and foster the addition of more advanced technology.