# CoKnowEMe: An Edge Evaluation Scheme for QoS of IoMT Microservices in 6G Scenario
## 1 Introduction
### A Complex and Dynamical Approach for a Context-Based Evaluation Model  
In this work, we propose a new evaluation scheme, which has been called Co-KnowEMe (context Knowledge evaluation model), modelling it following a complex and dynamical approach in accordance with the construction of IoMT services and taking into consideration the 6G paradigm and the healthcare scenario. The evaluation model consists of three different inter-operable levels. The different levels are based on the concepts of Acceptability, Usability and User Experience, which, combined together, allow a complete evaluation of the service, with both objective considerations, concerning the functional aspects and subjective ones, included through the study of user experience and the attributes that account for the interaction with the user. The evaluation model is presented as a dynamic model capable of conveying the knowledge acquired from each of the levels considered and from their combination. Moreover, for each level, several attributes and sub-attributes have been identified as the key aspects to be investigated with the aim of mining the knowledge referred to the different features considered. We propose a dynamical schematic evaluation model jointly with an analytical model for each level considered. The quantification of the outputs provided uses the Weighted Sum Model (WSM) [31], in which the weight of the values of the corresponding attributes is determined by the context of use. The context of use plays a key role within the model as it manages how to modulate the intensity of the attributes of each concept, increasing the effectiveness and accuracy of the evaluation and its adaptability to the interconnection of the different elements of the IoMT services. For this reason, the model is proposed as a context-based evaluation model. For the sake of clarity, we show the evaluation approach and the schematic representation in Figure 1 of a 6G scenario with heterogeneous sub-networks and systems and the plethora of entities from the mobile users and their devices (from wearable to hand-held) or the heterogeneous smart devices that form the IoT and IoMT networks. The aim of this representation is to schematically introduce a complex approach for both IoMT services and for the evaluation scheme, since each module can represent a resource in terms of data or computed output, in a multilevel architecture, which exploits the opportunity introduced by the edge intelligence. The 5G has already introduced a number of novel ideas to meet the stringent requirements set out, as, for example, heterogeneity, ultra-dense cells, mm-wave. The 6G network is expected to change the whole perspective of mobile communication networks by making the transformation from \"connected things\" or Internet of Things (IoT) or Internet from Everything to the \"connected intelligence\". Complex systems and Edge Intelligence (EI) [10; 16; 17; 18] powered by algorithms and techniques, such as machine learning, deep neural networks, diffusion dynamics and social network structure, are already being considered to be key missing elements in 5G networks. The upcoming 6G has the ambition to introduce heterogeneous and interconnected elements that can be represented by nodes of a complex network and can dynamically interact with each other as well as with their environment in an unpredictable and unplanned way. These ecosystems involve heterogenous devices with constrained resources and computational capabilities and call for novel algorithms and a new characterization for both dynamically managing and evaluating the lightweight services, as a microservice. Since we are rapidly moving from closed to open and distributed systems and to a completely dynamic topology that will be characterized by a vast heterogeneity, this requires an intelligence at edge level also for the evaluation of the services provided in order to introduce the same degree of adaptability [9; 10; 11; 12; 22]. Figure 1: Evaluation in a 6G scenario for IoMT microservices.