Розробка моделі розподілу задач віддаленого моніторингу здоров’я в розумному місті з урахуванням затримки, енергоспоживання та конфіденційності на fog-вузлах

The object of the research is the processes of dynamic distribution of computing tasks in multi-level infrastructures of a smart city. The possibilities of integrating edge, fog, and cloud computing resources for the development of remote patient monitoring systems (Remote Patient Monitoring, RPM) were investigated. The study addresses the challenge of balancing the rapid processing of critical medical signals with the limited energy resources of mobile devices. In addition, the need to ensure the confidentiality of personal data when transferring tasks to third-party fog nodes was addressed through encryption, remote attestation mechanisms, and isolated execution environments. A comprehensive system model was developed to describe the processes of performing RPM tasks (ECG classification, audio analysis). An offloading strategy was developed, based on a weighted linear to minimize energy consumption and delay. An architectural framework is proposed to ensure the confidentiality of data processing on uncontrolled fog nodes, through the use of Trusted Execution Environment (TEE) technologies and the deployment of Trusted Applications (TA). To validate the solutions, a series of simulations was conducted in the YAFS (Yet Another Fog Simulator) environment to compare Mobile, Hybrid, and Fog scenarios. It was experimentally established that transitioning to a Fog-oriented strategy results in a radical reduction in the average system latency (from 0.57 s to 0.027–0.030 s). The load on the smartphone is reduced by more than 10 times (from 222–225 mWh to 20.3–20.4 mWh), and the autonomy of wearable sensors increases almost fivefold. It is proven that the use of fog computing provides stable Quality of Service (QoS) on equipment with lower power (500 MIPS). The integration of attestation procedures according to RATS (Remote ATtestation procedureS) standard is intended to enable verification of the integrity of the computing stack before the transfer of confidential data.