The future of edge computing for healthcare ecosystem

Healthcare applications generate huge amounts of sensitive data which require proper storage, management, and analysis in order to derive meaningful information. Different computing solutions have been devised to store and process health data. Out of these, cloud computing has come to the forefront due to its capability to store and process massive amount of data. The data and processing applications are moving to the cloud owing to the benefits, such as on-demand scaling, reliability, and cost savings. However, the cloud platform can introduce latency challenges that can hamper performance of mission-critical applications, including violating several data privacy laws such as the Health Insurance Portability and Accountability Act (HIPAA). Edge computing is a new technology that promises to address these challenges by allowing devices in remote locations to process data locally at the “edge” of the network, either by the device or a local server, thereby achieving high computation, low latency, and data security requirements of the healthcare use cases. Though edge computing promises several benefits, it is a technology that is still in its infancy, and there are limitations on how much data can be processed at the edge, thereby making the choice of using edge computing challenging. In this chapter, we review the use of edge computing in healthcare. We performed a literature review to identify how edge computing has been used and the challenges it addresses, along with the opportunities that it creates. This chapter will be of interest to implementers and practitioners to understand the role of edge computing in the healthcare ecosystem.