We pointed recently to a discussion about the rise of edge computing, and as if on cue a recent report from Research and Markets has predicted the edge computing market will grow at a CAGR of 35 percent through 2022.
The increase is coming in response to the growth in data generated from multiple sources across different applications, the rise of real-time applications, and the increase of dependence on cloud infrastructure according to the report.
In healthcare, as more organizations collect data from connected medical, Internet of Things (IoT), mobile, and medical monitoring devices, it is increasingly difficult for some stakeholders to rationalize a centralized data repository for all healthcare data. Thus, healthcare edge computing is emerging as a way for entities to embrace near real-time results by processing data at the edge of the network at the data source.
Last year, a team of researchers associated with Michigan’s Wayne State University issued a report in the IEEE Internet of Things Journal which defined edge computing as “enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. The ‘edge’ is any computing and network resources along the path between data sources and cloud data centers.”
The increase of IoT devices and organizations putting more computing tasks into the cloud are the two major catalysts for edge computing in healthcare. Medical IoT devices are constantly collecting data and communicating with the network, and having actionable data in near real-time allows clinicians to make a more accurate diagnosis at the point of care, which can lead to a reduced number of return visits and save entities money.
“The demand of geographically distributed data processing applications, i.e., healthcare, requires data sharing and collaboration among enterprises in multiple domains,” the IEEE report authors explained. “To attack this challenge, collaborative edge can fuse geographically distributed data by creating virtual shared data views. . . An application will leverage this public interface to compose complex services for end users. These public services are provided by participants of collaborative edge, and the computation only occurs in the participant’s data facility such that the data privacy and integrity can be ensured.”