Data-sharing markets for integrating IoT data processing functionalities





Faculty/Professorship: Mobile Software Systems 
Author(s): Kasrin, Nasr ; Benabbas, Aboubakr  ; Elmamooz, Golnaz  ; Nicklas, Daniela  ; Steuer, Simon ; Sünkel, Michael  
Title of the Journal: CCF transactions on pervasive computing and interaction
ISSN: 2524-521X
Corporate Body: China Computer Federation (CCF)
Publisher Information: Singapore : Springer Singapore
Year of publication: 2021
Volume: 3
Issue: 1
Pages: 76-93
Language(s): English
DOI: 10.1007/s42486-020-00054-y
Abstract: 
The recent evolution of the Internet of Things into a cyber-physical reality has spawned various challenges from a data management perspective. In addition, IoT platform designers are faced with another set of questions. How can platforms be extended to smoothly integrate new data management functionalities? Currently, data processing related tasks are typically realized by manually developed code and functions which creates difficulties in maintenance and growth. Hence we need to explore other approaches to integration for IoT platforms. In this paper we cover both these aspects: (1) we explore several emerging data management challenges, and (2) we propose an IoT platform integration model that can combine disparate functionalities under one roof. For the first, we focus on the following challenges: sensor data quality, privacy in data streams, machine learning model management, and resource-aware data management. For the second, we propose an information-integration model for IoT platforms. The model revolves around the concept of a Data-Sharing Market where data management functionalities can share and exchange information about their data with other functionalities. In addition, data-sharing markets themselves can be combined into networks of markets where information flows from one market to another, which creates a web of information exchange about data resources. To motivate this work we present a use-case application in smart cities.
GND Keywords: Internet der Dinge; Informationssystem; Datenmanagement; Datenqualität; Privatsphäre; Maschinelles Lernen
Keywords: Internet of Things, Resource-Awareness, Infrastructure Design, Information Integration, Data Management Systems, Data Quality, Privacy, Machine Learning Model Management
DDC Classification: 004 Computer science  
RVK Classification: ST 270   
Peer Reviewed: Ja
International Distribution: Ja
Type: Article
URI: https://fis.uni-bamberg.de/handle/uniba/49611
Release Date: 4. March 2021