Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud

Currently, the use of biosensor-enabled mobile healthcare workflow applications in edge-cloud-enabled systems is increasing progressively. These are heavyweight and divided between a thin client device thick server edge cloud for execution. Application partitioning mechanism which based on resource energy parameters. However, existing application-partitioning schemes widely ignore security aspects applications. This study devises dynamic workload task-scheduling-secure (DAPWTS) algorithm framework that consists different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure schemes. The goal to minimize consumption nodes divide application local by applying secure algorithm. Furthermore, secure-min-cut aims migrate data form during system. After applications, node-search searches optimally run under their deadlines. maintain Simulation results show DAPWTS outperforms baseline approaches 30% terms consumption, deadline,