Modeling and Building IoT Data Platforms with Actor-Oriented Databases
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Modeling and Building IoT Data Platforms with Actor-Oriented Databases. / Wang, Yiwen; Dos Reis, Julio Cesar; Borggren, Kasper Myrtue; Vaz Salles, Marcos Antonio; Medeiros, Claudia Bauzer; Zhou, Yongluan.
Advances in Database Technology - EDBT 2019: 22nd International Conference on Extending Database Technology, Lisbon, Portugal, March 26-29, Proceedings . red. / Zoi Kaoudi; Helena Galhardas; Irini Fundulaki; Berthold Reinwald; Melanie Herschel; Carsten Binnig. OpenProceedings.org, 2019. s. 512-523.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - Modeling and Building IoT Data Platforms with Actor-Oriented Databases
AU - Wang, Yiwen
AU - Dos Reis, Julio Cesar
AU - Borggren, Kasper Myrtue
AU - Vaz Salles, Marcos Antonio
AU - Medeiros, Claudia Bauzer
AU - Zhou, Yongluan
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85064947935&partnerID=8YFLogxK
U2 - 10.5441/002/edbt.2019.47
DO - 10.5441/002/edbt.2019.47
M3 - Article in proceedings
AN - SCOPUS:85064947935
SP - 512
EP - 523
BT - Advances in Database Technology - EDBT 2019
A2 - Kaoudi, Zoi
A2 - Galhardas, Helena
A2 - Fundulaki, Irini
A2 - Reinwald, Berthold
A2 - Herschel, Melanie
A2 - Binnig, Carsten
PB - OpenProceedings.org
T2 - 22nd International Conference on Extending Database Technology, EDBT 2019
Y2 - 26 March 2019 through 29 March 2019
ER -
ID: 218221279