Modeling and Building IoT Data Platforms with Actor-Oriented Databases

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  • Yiwen Wang
  • Julio Cesar Dos Reis
  • Kasper Myrtue Borggren
  • Marcos Antonio Vaz Salles
  • Claudia Bauzer Medeiros
  • Zhou, Yongluan

Vast amounts of data are being generated daily with the adoption of Internet-of-Things (IoT) solutions in an ever-increasing number of application domains. There are problems associated with all stages of the lifecycle of these data (e.g., capture, curation and preservation). Moreover, the volume, variety, dynamicity and ubiquity of IoT data present additional challenges to their usability, prompting the need for constructing scalable data-intensive IoT data management and processing platforms. This paper presents a novel approach to model and build IoT data platforms based on the characteristics of an Actor-Oriented Database (AODB). We take advantage of two complementary case studies – in structural health monitoring and beef cattle tracking and tracing – to describe novel software requirements introduced by IoT data processing. Our investigation illustrates the challenges and benefits provided by AODB to meet these requirements in terms of modeling and IoT-based systems implementation. Obtained results reveal the advantages of using AODB in IoT scenarios and lead to principles on how to effectively use an actor model to design and implement IoT data platforms.

Original languageEnglish
Title of host publicationAdvances in Database Technology - EDBT 2019 : 22nd International Conference on Extending Database Technology, Lisbon, Portugal, March 26-29, Proceedings
EditorsZoi Kaoudi, Helena Galhardas, Irini Fundulaki, Berthold Reinwald, Melanie Herschel, Carsten Binnig
Publication date2019
ISBN (Electronic)9783893180813
Publication statusPublished - 2019
Event22nd International Conference on Extending Database Technology, EDBT 2019 - Lisbon, Portugal
Duration: 26 Mar 201929 Mar 2019


Conference22nd International Conference on Extending Database Technology, EDBT 2019

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