Model-driven Self-adaptive Deployment of Internet of Things Applications with Automated Modification Proposals

Abstract

Today’s Internet of Things (IoT) applications are mostly developed as a bundle of hardware and associated software. Future cross-manufacturer app stores for IoT applications will require that the strong coupling of hardware and software is loosened. In the resulting IoT applications, a quintessential challenge is the effective and efficient deployment of IoT software components across variable networks of heterogeneous devices. Current research focuses on computing whether deployment requirements fit the intended target devices instead of assisting users in successfully deploying IoT applications by suggesting deployment requirement relaxations or hardware alternatives. This can make successfully deploying large-scale IoT applications a costly trial-and-error endeavor. To mitigate this, we have devised a method for providing such deployment suggestions based on search and backtracking. This can make deploying IoT applications more effective and more efficient, which, ultimately, eases reducing the complexity of deploying the software surrounding us.

Model‐based digital twins of medicine dispensers for healthcare IoT applications

“…There are approaches for testing IoT applications, 45 handle privacy violations in IoT clouds, 46 mutation testing of IoT applications, 47 and cost-effective deployment and testing of IoT clouds. 48 Some approaches utilize DTs for anomaly detection in healthcare IoT systems, 3 industrial IoT systems, 49 and CPSs. 4,50 Compared to these works, our approach aims to facilitate automated testing of healthcare IoT applications using DTs in place of medical dispensers.…”

Software Testing Using Cutting-Edge Technologies With Supporting Knowledge Managment: A Survey

“…The majority of Internet of Things (IoT) applications developed today come in the form of hardware and related software modules. Future cross-manufacturer IoT app shops will need to loosen the tight link between hardware and software [68]. The Raspberry Pi is used in IoT as an edge device that links different sensors to show data processing results.…”

“…[15], [18], [19], [20], [21], [23], [34], [44], [67] C4 Raspberry Pi robotic programming 14 16 [22], [23], [25], [32], [35], [36], [39], [66], [68], [71], [73], [74], [75], [76] Sum 88 1. Building a knowledge repository for all test case scenarios and storing data related to each software project component.…”