Moving towards Smart Cities: A Selection of Middleware for Fog-to-Cloud Services

Abstract

Smart cities aim at integrating various IoT (Internet of Things) technologies by providing many opportunities for the development, governance, and management of user services. One of the ways to support this idea is to use cloud and edge computing techniques to reduce costs, manage resource consumption, enhance performance, and connect the IoT devices more effectively. However, the selection of services remains a significant research question since there are currently different strategies towards cloud computing, including services for central remote computing (traditional cloud model) as well as distributed local computing (edge computing). In this paper, we offer an integrated view of these two directions and the selection among the edge technologies based on MCDA (Multiple Criteria Decision Analysis) algorithms. To this end, we propose a foglet as a middleware that aims at achieving satisfactory levels of customer services by using fuzzy similarity and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to facilitate the rating and selection of services in the fog-to-cloud environment. Then, we describe the selection process with a numerical example, and conclude our work with an outline of future perspectives.

Keywords

• fog computing
• cloud computing
• edge computing
• smart services
• smart cities
• IoT
• fuzzy similarity
• TOPSIS
• MCDA approaches