Combining Fog and Cloud Computing to Support Spatial Analytics in Smart Cities

Abstract

Spatial data generated by an Internet of Things (IoT) network is important to assist the spatial analytics process in issues related to smart cities. In these cities, IoT devices generate spatial data constantly. Thus, data can get increasingly voluminous very fast. In this paper, we investigate the challenge of managing these data through the use of a spatial data warehouse designed over a parallel and distributed data processing framework extended with a spatial analytics system. We propose an architecture aimed to assist a smart cities manager in the decision-making process. This architecture integrates a cloud layer where these technologies are located with a fog computing layer for extracting, transforming and loading the data into the spatial data warehouse. Furthermore, we introduce a set of guidelines to aid smart cities managers to implement the proposed architecture. These guidelines describe and discuss important issues that should be faced by the managers. We validate our architecture with a case study that uses real data collected by IoT devices in a smart city. This case study encompasses the execution of three different categories of spatial queries, demonstrating the architecture's efficacy and effectiveness to support spatial analytics in the context of smart cities.

Multi-Layer Fog-Cloud Architecture for Optimizing the Placement of IoT Applications in Smart Cities

“…Constraint (10) calculates the processing conditions of IoT application i ∈ I of both cloud and fog layers, while constraint (11) calculates the entire processing of both cloud and fog layers d ∈ N.…”

“…Thus, there is a need for an efficient optimization approach to place and process IoT applications either in the fog, in the cloud, or both, depending on their requirements. Some of the related works in the field of smart cities have focused on the execution of IoT applications and services, as presented in [1,2,[4][5][6][7][8][9][10]. For example, Belli et al [5] have highlighted the key factors of an IoT infrastructure for smart cities along with their challenges.…”

“…However, their work was relied on the capacity of IoT devices, and any limited access to these devices would impact the performance of their proposed framework. Moreover, Clarindo et al [10] introduced a three-layer architecture in the context of smart cities that helps a smart city manager to analyze IoT data and perform a decision-making process. However, all the listed works have not considered the cost of resource usage, power consumption, and service latency in multi-layer environments.…”