Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

Abstract

Layered internet of things (IoT) architectures have been proposed over the last years as they facilitate understanding the roles of different networking, hardware, and software components of smart applications. These are inherently distributed, spanning from devices installed in the field up to a cloud datacenter and further to a user smartphone, passing by intermediary stages at different levels of fog computing infrastructure. However, IoT architectures provide almost no hints on where components should be deployed. IoT Software Platforms derived from the layered architectures are expected to adapt to scenarios with different characteristics, requirements, and constraints from stakeholders and applications. In such a complex environment, a one-size-fits-all approach does not adapt well to varying demands and may hinder the adoption of IoT Smart Applications. In this paper, we propose a 5-layer IoT Architecture and a 5-stage IoT Computing Continuum, as well as provide insights on the mapping of software components of the former into physical locations of the latter. Also, we conduct a performance analysis study with six configurations where components are deployed into different stages. Our results show that different deployment configurations of layered components into staged locations generate bottlenecks that affect system performance and scalability. Based on that, policies for static deployment and dynamic migration of layered components into staged locations can be identified.

Characterization of Low-Cost Capacitive Soil Moisture Sensors for IoT Networks

“…A distinct advantage of wireless transmission is a significant reduction and simplification in wiring and harness, a required feature for smart farming [10,11], where installation flexibility for sensors is not an option. A description of a modular IoT architecture for several applications including but not limited to healthcare, health monitoring, and precision agriculture is reported in previous works [12,13].…”

Evaluation of the Use of Class B LoRaWAN for the Coordination of Distributed Interface Protection Systems in Smart Grids

“…The success of LoRaWAN is demonstrated by the huge literature available. In particular, some works already highlighted the tradeoff between the application update rate and the number of nodes in a network [21,22]. However, it has to be highlighted that most of the results are limited to Class A devices, whereas very few extend the analysis to Class B [23,24].…”

BIoTA: A Buildout IoT Application Language

“…There is a set of preconfigured connection rules that dictate how components can be connected, which can be created, read, updated, and deleted by users at their discretion. An initial set of preconfigured rules carry the knowledge acquired by the authors in their experience in different IoT software architectures [3], [5], [32], [74], [75], [77], [78]. Figure 16 shows the components and connectors related to the smart parking scenario and its software architecture dis-cussed in Section VI-A by using the BIoTA IDE.…”

“…Also, mapping hardware devices into corresponding software components highlights another level of intrinsic complexity involved in IoT software architectures. Although there are already some initiatives to create these architectures, they still need wide acceptance by the community of software developers [2], [5]. IoT application developers need to use an integrated development environment (IDE) based on a domain-specific high-level language that abstracts the definition of components and connectors [6], [7].…”