Data Dissemination Techniques for Internet of Things Applications: Research Challenges and Opportunities

Lenando, Halikul bin; Albert, Sanjay Charles; Alrfaay, Mohamad

doi:10.2478/fcds-2024-0017

Abstract

The escalating prevalence of Internet of Things (IoT) devices has necessitated efficient data dissemination methods to optimize the unprecedented volume of generated data. The rapid expansion of IoT devices and the resulting surge in data creation underscore the necessity for advanced data dissemination methods. A noticeable gap in existing literature prompts a critical review, specifically addressing challenges and opportunities in IoT data dissemination techniques. This paper aims to categorize and analyze existing data dissemination techniques, highlighting their strengths and limitations. Additionally, it explores emerging opportunities and innovations that can shape the future of IoT applications. Furthermore, the discussion addresses challenges in data dissemination and explores innovative solutions, including machine learning, AI-based strategies, edge, and fog computing, blockchain integration, and advanced 5G/6G networks. The hope is that this study sets the stage for innovative ideas contributing to the efficiency and robustness of IoT applications, informing future endeavours in this dynamic and evolving landscape.

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Data Dissemination Techniques for Internet of Things Applications: Research Challenges and Opportunities

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