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Data-Centric Network of Things: A Method for Exploiting the Massive Amount of Heterogeneous Data of Internet of Things in Support of Services
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
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 [en]
Internet of Things, Big Data, Artificial Intelligence, Data Supply, Distributed System
National Category
Computer Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-142342ISBN: 978-91-7649-840-8 (print)ISBN: 978-91-7649-841-5 (electronic)OAI: oai:DiVA.org:su-142342DiVA: diva2:1092194
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
List of papers
1. Constructing Context-centric Data Objects to Enhance Logical Associations for IoT Entities
Open this publication in new window or tab >>Constructing Context-centric Data Objects to Enhance Logical Associations for IoT Entities
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.

Keyword
IoT Entity Associations, Service Logics, Ontology, Data Object Construction, Event Net
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-120244 (URN)10.1016/j.procs.2015.05.124 (DOI)
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
2. Logical interactions for heterogeneous IoT entities via virtual world mirrors in support of Ambient Assisted Living
Open this publication in new window or tab >>Logical interactions for heterogeneous IoT entities via virtual world mirrors in support of Ambient Assisted Living
2016 (English)In: Journal of Ambient Intelligence and Smart Environments, ISSN 1876-1364, E-ISSN 1876-1372, Vol. 8, no 5, 565-580 p.Article in journal (Refereed) Published
Abstract [en]

In Ambient Assisted Living (AAL), as an important applied area of Internet of Things (IoT) technology, logical entity interaction establishes an intelligent virtual world in which heterogeneous entities are emulated by object-oriented mirrors through tightly cooperating sensors and actuators from different spaces in the real world; this enables the system to generate intelligent services to support human behaviour. However, until now, few researchers have focused on enabling interactions between heterogeneous IoT entities for AAL services. Further, in relevant studies regarding semantic entity interactions, researchers have mainly focused on enabling semantic interactions between sensors (rather than integral entities) for the purpose of coordinating and managing data resources, where tight collaborations between sensors and actuators are not emphasised. Hence, the system capability of initialising intelligent service to enhance human experience has not been properly emphasised, to date. This paper discusses enabling logical object-oriented IoT entity interactions to enrich AAL services for humans through the creation of mirrors in the virtual world emulating the attributes and behaviours of heterogeneous entities via cooperating sensors and actuators in the real world. This paper introduces the Entity Device Collocating (EDC) Platform to globally locate and retrieve sensors and actuators respectively adhering to the attributes and behaviours of integral mirrors in the virtual world; this is intended to enable the interoperability between virtual and real worlds. Interactions are created upon entity mirrors mapping entities from the physical world to the virtual world, during which interactions continue to evolve based on the service logics. The proposed technique is applied to a typical AAL case of smart pill-ingestion, where a demo is implemented for verification. Comparing with relevant research, the proposed technique contributes by introducing a flexible and scalable IoT entity interaction method targeting AAL to address human needs.

Keyword
Logical object-oriented interaction, service logics, semantics, Ambient Assisted Living, Internet of Things
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-137780 (URN)10.3233/AIS-160398 (DOI)000388210700008 ()
Available from: 2017-01-11 Created: 2017-01-10 Last updated: 2017-05-11Bibliographically approved
3. Intelligent Data-Intensive IoT: A Survey
Open this publication in new window or tab >>Intelligent Data-Intensive IoT: A Survey
Show others...
2016 (English)In: 2016 2nd IEEE International Conference on Computer and Communications (ICCC): Proceedings, IEEE Computer Society, 2016, 2362-2368 p.Conference paper, Published paper (Refereed)
Abstract [en]

The IoT paradigm proposes to connect entities intelligently with massive heterogeneous nature, which forms an ocean of devices and data whose complexity and volume are incremental with time. Different from the general big data or IoT, the data-intensive feature of IoT introduces several specific challenges, such as circumstance dynamicity and uncertainties. Hence,intelligence techniques are needed in solving the problems brought by the data intensity. Until recent, there are many different views to handle IoT data and different intelligence enablers for IoT, with different contributions and different targets. However, there are still some issues have not been considered. This paper will provide a fresh survey study on the data-intensive IoT issue. Besides that, we conclude some shadow issues that have not been emphasized, which are interesting for the future. We propose also an extended big data model for intelligent data-intensive IoT to tackle the challenges.

Place, publisher, year, edition, pages
IEEE Computer Society, 2016
Keyword
intelligence enabler, data provision, internet of things, data-intensive, context
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-137479 (URN)10.1109/CompComm.2016.7925122 (DOI)978-1-4673-9026-2 (ISBN)
Conference
2016 2nd IEEE International Conference on Computer Communications, Chengdu, China, 14-17 October, 2016
Available from: 2017-01-08 Created: 2017-01-08 Last updated: 2017-06-22Bibliographically approved
4. Edge-based Interoperable Service-driven Information Distribution for Intelligent Pervasive Services
Open this publication in new window or tab >>Edge-based Interoperable Service-driven Information Distribution for Intelligent Pervasive Services
(English)In: Pervasive and Mobile Computing, ISSN 1574-1192, E-ISSN 1873-1589Article in journal (Refereed) Submitted
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-142339 (URN)
Available from: 2017-05-01 Created: 2017-05-01 Last updated: 2017-05-11Bibliographically approved
5. A Deep Relation Learning Method for IoT Interoperability Enhancement within Semantic Formalization Framework
Open this publication in new window or tab >>A Deep Relation Learning Method for IoT Interoperability Enhancement within Semantic Formalization Framework
2016 (English)Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2016
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-142338 (URN)
Conference
International conference on Internet of Things, Data and Cloud Computing, Cambridge, United Kingdom, March 22 - 23, 2016
Available from: 2017-05-01 Created: 2017-05-01 Last updated: 2017-06-22
6. Self-evolvable Knowledge-enhanced IoT Data Mobility for Smart Environments
Open this publication in new window or tab >>Self-evolvable Knowledge-enhanced IoT Data Mobility for Smart Environments
(English)Article in journal (Refereed) Submitted
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-142340 (URN)
Available from: 2017-05-01 Created: 2017-05-01 Last updated: 2017-05-11Bibliographically approved

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