Characterising edge-cloud data transmission for patient-centric healthcare systems

Benefiting from the modern information and communication technologies, the healthcare provisioning is actively evolving along a trend toward patient centricity, and the de facto solution seems to be technological collaboration and cooperation within a three-tier architecture. Given the largely distributed tiers and the components, a hot research focus is on minimizing the data transmission latency to improve the quality of healthcare services, especially in the time-critical situations. It has been identified that a typical performance bottleneck is the communication between the last two tiers that are generally represented by the edge and the cloud nowadays. Thus, optimising the edge-cloud data traffic becomes valuable and crucial to addressing the performance bottleneck, while characterising the edge-cloud data transmission plays a prerequisite role in the optimisation efforts. Unlike the existing studies that mainly emphasise the intuitive features (e.g., the overall big data volume), our work argues and reveals the importance of identifying the practical characteristics of edge-cloud data transmission at runtime, w.r.t. different workload regimes and heterogeneous edge nodes.