# An Architecture for the Performance Management of Smart Healthcare Applications
## 1 Introduction  
Computational intelligence and the Internet of Things (IoT) evolve along with the advances of next-generation wireless technologies, such as 5G and 6G cellular networks [1]. This evolution has boosted the development of traditional healthcare into the Internet of Medical Things (IoMT) and smart healthcare (s-health) services [2]. S-health is essential to both patients and healthcare practitioners. Once it improves treatments, it enables the remote patient monitoring, enhances the patient quality of life, and reduces costs. Forecasts show a growing market for s-health of 12.5% until 2025 [3]. However, s-health applications include a wide range of services, such as critical care monitoring and remote surgery, requiring low-latency and high-reliability communication to transmit data to healthcare professionals promptly and patients [4, 5]. Managing network resources may improve reliability and latency, and it seems to be an efficient way to achieve s-health requirements. If low-latency and high-reliability are not achieved, s-health services are degraded, leading even to their denial. High-reliability means successful data transmission without extrapolating the maximum latency supported by the s-health application [6]. Achieving the performance requirements is not a trivial task since s-health applications rely on a heterogeneous communication environment. Regulatory institutions (e.g., the U.S. Food and Drug Administration) reinforce the development of reliable health devices and applications [7] by acts as the Health Insurance Portability and Accountability Act (HIPAA). Furthermore, the network traffic diversity has grown exponentially due to 5G, the advent of 6G, and IoMT smart scenarios (e.g., smart hospital) that daily generate a massive amount of data, resulting in high complexity to support s-health application requirements. The variety of s-health applications (e.g., telemedicine, critical care monitoring) makes the task even more complicated since each application has specific requirements [8]. For instance, remote surgery requires reliability of 99.999% and latency of 1 ms, while continuous monitoring of noncritical patients support 125 ms of latency [5; 9]. Performance management leads to improvements in s-health applications by adjusting or tuning network resources (e.g., bandwidth, and memory) to application needs, once the improper use of network resources results in latency and reliability degradation, and unsatisfactory Quality of Service. The high level of reliability demanded by s-health applications reveals limitations in traditional network mechanisms (e.g., priority queues) given traffic diversity and volume [8; 10; 11]. Current network technologies are not prepared to deal with such amount of data and devices, since they do not support the dynamics and on-demand network resource allocation. For instance, the IEEE 802.11 standard has four access categories to give priority to different types of traffic (e.g., voice, video) [12]. Nonetheless, health-related traffic uses the same category as voice traffic. Another work has created a special priority for medical alerts [13; 14; 15; 16]. However, the latency required by s-health application is not yet achieved. The recent network slicing paradigm is a potential solution for performance management on s-health since it contains essential features, such as automation, fast adaptation, and customization [5]. Although such concept is addressed in the literature [17; 18; 19; 15], the implementation of a realistic network slicing environment is often not presented. Moreover, solutions that tailor network resources (e.g., define a fixed amount of resources) to transmit only health data packets are unique to one type of application [13; 14]. Therefore, it is indispensable new ways to manage the amount of network traffic, adapt network resources (e.g., change the link used by the application according to the bandwidth available), reach specific requirements, and then support s-health [20].