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Constructing Context-centric Data Objects to Enhance Logical Associations for IoT Entities
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2015 (English)In: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 52, 1095-1100 p.Article in journal (Refereed) Published
Abstract [en]

Entities in Internet of Things (IoT) need intelligent associations to allow a flexible and dynamic system reaction towards varying user situations. Purely data-oriented association methods (e.g., data-mining, machine-learning, etc.) are limited in deduction from existing associations. Also such data-oriented methods are limited in accuracy for working with small-scale datasets (e.g., working with patterns retrieved from historical data), outputting associations based on statistics rather than logic. Moreover, existing semantic technologies (ontological-oriented or rule-oriented) are facing with either flexibility or dynamicity challenges to discover and maintain the associations. This paper proposes an alternative technique of semantically constructing context-centric data objects based on service logics for logical associations, which enables an event net based on association nets adapting for the changing situations (called context-centric). A proof-of-concept implementation is carried out based on a vehicle planning scenario to validate the data construction technique. Comparing to previous work, this technique possesses advantages of flexibility and dynamicity for entity associations based on service logics.

Place, publisher, year, edition, pages
2015. Vol. 52, 1095-1100 p.
Keyword [en]
IoT Entity Associations, Service Logics, Ontology, Data Object Construction, Event Net
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-120244DOI: 10.1016/j.procs.2015.05.124OAI: oai:DiVA.org:su-120244DiVA: diva2:851027
Conference
The 5th International Symposium on Internet of Ubiquitous and Pervasive Things (IUPT 2015), London, United Kingdom, June 2-5, 2015
Available from: 2015-09-03 Created: 2015-09-03 Last updated: 2017-06-29Bibliographically approved
In thesis
1. Data-Centric Network of Things: A Method for Exploiting the Massive Amount of Heterogeneous Data of Internet of Things in Support of Services
Open this publication in new window or tab >>Data-Centric Network of Things: A Method for Exploiting the Massive Amount of Heterogeneous Data of Internet of Things in Support of Services
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Internet of things (IoT) generates massive amount of heterogeneous data, which should be efficiently utilized to support services in different domains. Specifically, data need to be supplied to services by understanding the needs of services and by understanding the environment changes, so that necessary data can be provided efficiently but without overfeeding. However, it is still very difficult for IoT to fulfill such data supply with only the existing supports of communication, network, and infrastructure; while the most essential issues are still unaddressed, namely the heterogeneity issue, the recourse coordination issue, and the environments’ dynamicity issue. Thus, this necessitates to specifically study on those issues and to propose a method to utilize the massive amount of heterogeneous data to support services in different domains.

This dissertation presents a novel method, called the data-centric network of things (DNT), which handles heterogeneity, coordinates resources, and understands the changing IoT entity relations in dynamic environments to supply data in support of services. As results, various services based on IoT (e.g., smart cities, smart transport, smart healthcare, smart homes, etc.) are supported by receiving enough necessary data without overfeeding.

The contributions of the DNT to IoT and big data research are: firstly the DNT enables IoT to perceive data, resources, and the relations among IoT entities in dynamic environments. This perceptibility enhances IoT to handle the heterogeneity in different levels. Secondly, the DNT coordinates IoT edge resources to process and disseminate data based on the perceived results. This releases the big data pressure caused by centralized analytics to certain degrees. Thirdly, the DNT manages entity relations for data supply by handling the environment dynamicity. Finally, the DNT supply necessary data to satisfy different service needs, by avoiding either data-hungry or data-overfed status.

Place, publisher, year, edition, pages
Stockholm: Department of Computer and Systems Sciences, Stockholm University, 2017. 44 p.
Series
Report Series / Department of Computer & Systems Sciences, ISSN 1101-8526 ; 17-006
Keyword
Internet of Things, Big Data, Artificial Intelligence, Data Supply, Distributed System
National Category
Computer Systems
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-142342 (URN)978-91-7649-840-8 (ISBN)978-91-7649-841-5 (ISBN)
Public defence
2017-06-13, Lilla hörsalen, NOD-huset, Borgarfjordsgatan 12, Kista, 13:00 (English)
Opponent
Supervisors
Available from: 2017-05-19 Created: 2017-05-01 Last updated: 2017-05-22Bibliographically approved

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