Enhancing Older Adults’ Well-Being Through QoS-Aware Edge-Cloud eHealth Applications

Ensuring the well-being of older adults using eHealth applications has become increasingly important. Continuous health monitoring, emergency response, and various personalized applications can improve the well-being of the older adults through intelligent and adaptive data processing. But, the effectiveness of such systems highly depends on the provisioning of efficient computing resources that meet Quality of Service (QoS) requirements (of the applications), including low latency, faster computation, reliability, and security. Leveraging Edge-Cloud Computing can offer a promising solution but an effective strategy is required to understand the Quality of Service (QoS) requirements of applications while offloading in Edge-Cloud Computing. Previous research lacks in focusing predicted behaviour of application workloads (and related QoS) while scheduled on the Edge-Cloud platform. This research addresses this issue by proposing a scalable model facilitating resource allocation based on the specific future requirements of data processing tasks. In this research, an efficient heuristic algorithm is developed to maximize meeting the QoS constraints. The effectiveness of the proposed approach is evaluated through simulations comparing its performance against existing methods, thereby facilitating improved service delivery and user satisfaction.