Sensor Observation Streams within Cloud-Based IoT Platforms: Challenges and Directions

Antoine Auger , Ernesto Expósito (1) , Emmanuel Lochin (2)

1 LIUPPA - Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour
2 DMIA - Département de Mathématiques, Informatique, Automatique

Observation streams can be considered as a special case of data streams produced by sensors. With the growth of the Internet of Things (IoT), more and more connected sensors will produce unbounded observation streams. In order to bridge the gap between sensors and observation consumers, we have witnessed the design and the development of Cloud-based IoT platforms. Such systems raise new research challenges, in particular regarding observation collection, processing and consumption. These new research challenges are related to observation streams and should be addressed from the implementation phase by developers to build platforms able to meet other non-functional requirements later. Unlike existing surveys, this paper is intended for developers that would like to design and implement a Cloud-based IoT platform capable of handling sensor observation streams. It provides a comprehensive way to understand main observation-related challenges, as well as non-functional requirements of IoT platforms such as platform adaptation, scalability and availability. Last but not the least, it gives recommendations and compares some relevant open-source software that can speed up the development process.

Keywords: Index Terms-Internet of Things; sensors; observations; streams; Quality of Information; Autonomic Computing; Cloud Computing; Software Architecture Patterns

Domains: Computer Science [cs]

Antoine Auger, Ernesto Expósito, Emmanuel Lochin. Sensor Observation Streams within Cloud-Based IoT Platforms: Challenges and Directions. 20th Conference on Innovations in Clouds, Internet and Networks, ICIN 2017, Paris, France, March 7-9, 2017, Mar 2017, Paris, France. pp.177-184, ⟨10.1109/ICIN.2017.7899407⟩. ⟨hal-01908065⟩