- The integration of Internet of Things (IoT) devices and analytics solutions put a lot of strain on siloed health IT infrastructure as more computing power is needed. As a result, edge computing and fog computing are becoming ways for entities to better leverage their technology for a decentralized approach to data analytics.
Fog and edge computing cater to IoT devices. Traditionally, data is produced at the edge of the network and transported back to the datacenter. Edge and fog computing process the data at the source or the edge of the network. The network edge is any computing and network resources along the path between data sources and cloud data centers.
Fog and edge computing increase operational efficiency by allowing end users to access smaller, more specific data instead of accessing information in a centralized, cloud-based infrastructure along with data they will never need to access.
Breaking down the access of data into fog layers gives large healthcare organizations a more organized approach to retrieve relevant data so analytics can be performed on the edge of the network in near real-time.
In response to the growing demand for edge computing, the OpenFog Consortium announced that its OpenFog Reference Architecture will be the basis of a new IEEE Standards Association (IEEE-SA) working group.
The working group’s purpose is to innovate fog computing faster so more organizations can adopt it sooner. The group is focusing on developing fog and edge computing for the IoT and 5G embedded artificial intelligence applications.
“This represents a giant step forward for fog computing and for the industry, which will soon have the specifications for use in developing industrial strength fog-based hardware, software and services,” IEEE Standards Working Group on Fog Computing and Networking Architecture Framework Chair John Zao said in a statement. “The objective from the beginning was that the OpenFog Reference Architecture would serve as the high-level basis for industry standards, and the IEEE is looking forward to the collaboration in this effort.”
The OpenFog Architecture is a technical framework that will help developers build out fog computing solutions that will support the data-intensive requirements of the IoT and AI applications. The framework has a horizontal system architecture for distributing computing, storage, control, and networking functions closer to the edge of the network where the data is produced.
The framework distributes information technology, communication technology, and operational technology services through an information messaging infrastructure.
“The mandate for fog computing is growing stronger, driven by the recognition that traditional architectures can’t deliver on the operational challenges for today’s advanced digital applications,” OpenFog Consortium Chairman and Senior Director Helder Antunes said in a statement. “On behalf of the members of the OpenFog technical community, I’m pleased to see the recognized value of the OpenFog Reference Architecture and IEEE’s commitment to fog computing and networking via the formation of this new working group.”
A report released by Research and Markets outlined the growth of fog computing, indicating that the healthcare vertical is expected to see increased operational efficiency due to fog computing for connected medical and IoT devices.
Report analysts predicted the fog computing market to grow at a CAGR of 60 percent from 2017 to 2021. The rapid growth rate is due to organizations needing a faster and more convenient way for end users to access the data constantly produced by connected and IoT devices.
The current digitization of healthcare lends itself to fog and edge computing as the technology allows clinicians to collect and analyze data in near real-time. As the number of IoT devices continues to grow, edge and fog computing may become a standard in health IT infrastructure.