THE ROLE OF DEPENDABILITY IN IOT SYSTEMS

Authors

  • Mohammad Ibraigheeth Bethlehem University

Keywords:

internet of things (IoT),, dependability, reliability, resource constrains, failure recovery

Abstract

The advances in the Internet of Things (IoT) have contributed to the automation of various industries by enabling devices and systems to effectively connect and collect data remotely over the internet. This progress has led to the creation of an intelligent society where physical things are becoming increasingly innovative and undoubtedly, the IoT systems will continue to impact real life by providing efficient data collection and sharing. The successful implementation of IoT systems relies on their dependability, which is closely tied to several factors such as their reliability, resilience, and security. This paper explores the crucial role of dependability in IoT system, emphasizing challenges such as real-time analysis, resource constrains, connection redundancy, and quick fault recovery. The paper also provides some strategies for overcoming dependability challenges, such as efficient algorithms, edge computing, prioritization of resources, and AI techniques integration. Additionally, the paper presents a case study of an IoT system that faced dependability problems, highlighting the importance of rigorous testing and redundancy in ensuring reliable IoT deployments.  As a result of this research, we suggest that by addressing the challenges related to dependability aspects, stakeholders can unlock the full potential of IoT, empowering industries and individuals with transformative, efficient, and reliable technologies. For future work, a frame work for evaluating and enhancing the IoT dependability will be developed. Several factors will be considered in developing this framework, such as reliability, availability, safety, security, resilience, and fault management. The framework will define a quantifiable metrics to measure these factors.

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Published

2024-01-03 — Updated on 2024-01-08

Versions

Issue

Vol. 1 No. 2 (2023): Journal of Intelligent Systems and applied data science (JISADS)

Section

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