Multi-criteria Decision Making and Soft Computing for the Selection of Specialized IoT Platform

The task of the appropriate selection of the specialized Internet of Things (IoT) platform is very relevant today. The complexity of the selection process is due to (a) the large number of IoT platforms, which are available on the IoT services market, and (b) the variety of services and features, which they offer. In this paper, the multi-criteria decision making (MCDM) and the soft computing approaches for choosing the specialized IoT platform are considered. Authors illustrate solving MCDM problem using the linear convolution method with simple ranking approach to forming weight coefficients for criteria. MCDM methods have some limitations: (a) the need to take into account weight coefficients of the criteria; (b) the composition of the Pareto-optimal set of alternative decisions; (c) the lack of ability to change the dimension of the vector of alternatives and criteria in real time; (d) significant impact of weight coefficients that the expert determines on the result. Thus, the authors propose to use the soft computing approach, in particular, Mamdani-type fuzzy logic inference engine for selection of the specialized IoT platform. Relevant factors (reliability, dependability, safety, and security of IoT platforms) are considered as the most important ones for decision making in the IoT platform selection processes. In addition, analysis and research of the influence level of various factors on the selection of specialized IoT platform have been carried out. Special cases of choosing the specialized IoT platform with confirmation of the appropriateness of the using soft computing approach are discussed.