Invited Paper: Semantic IoT Data Description and Discovery in the IoT-Edge-Fog-Cloud Infrastructure

dc.contributor.authorZeng, Wenxi
dc.contributor.authorZhang, Shuai
dc.contributor.authorYen, I-Ling
dc.contributor.authorBastani, Farokh B.
dc.contributor.utdAuthorZeng, Wenxi
dc.contributor.utdAuthorZhang, Shuai
dc.contributor.utdAuthorYen, I-Ling
dc.contributor.utdAuthorBastani, Farokh B.
dc.date.accessioned2020-04-06T21:04:46Z
dc.date.available2020-04-06T21:04:46Z
dc.date.issued2019-04-04
dc.descriptionDue to copyright restrictions and/or publisher's policy full text access from Treasures at UT Dallas is limited to current UTD affiliates (use the provided Link to Article).
dc.description.abstractMany IoT systems are data intensive, where a large volume of data steadily get generated from a large number of sensors in the system. These data are continuous, thus, how to store and manage them is an important issue. Existing time series databases (TSDBs) offer some good strategies for storing continuous IoT data streams, but they lack a good semantic model for describing the IoT data streams to support effective data discovery. This shortcoming becomes critical when we consider the need for data sharing in many application domains; and it becomes significant when we consider the super huge scale of the IoT-Edge-Fog-Cloud infrastructure and the dynamic data flows in the infrastructure. In this paper, we develop the solutions for IoT data management in the IoT-Edge-Fog-Cloud infrastructure. We focus on the issues of data storage, specification and discovery. First, we build a semantic model for better specification of the IoT data streams (time series data), the DS-ontology. We have applied DS-ontology to TSDBs and developed the SE-TSDB tool suite, which runs on top of existing TSDBs to help establish semantic specifications for data streams and enable semantic-based data retrievals. We have also developed the IoT data discovery techniques based on SE-TSDB to facilitate semantic based data retrieval in the IoT-Edge-Fog-Cloud infrastructure. With our techniques, IoT data streams can be more effectively tracked and flexibly retrieved to help with integrated data analytics and improved knowledge discovery. © 2019 IEEE.
dc.description.departmentErik Jonsson School of Engineering and Computer Science
dc.description.sponsorshipNational Science Foundation (NSF) Industry/University Collaborative Research Center (1/UCRC) Award No. IIP-1361795
dc.identifier.bibliographicCitationZeng, W., S. Zhang, I. -L Yen, and F. Bastani. 2019. "Invited paper: Semantic IoT data description and discovery in the IoT-Edge-Fog-Cloud infrastructure."IEEE International Conference on Service-Oriented System Engineering: 106-115, doi: 10.1109/SOSE.2019.00024
dc.identifier.isbn9781728114415
dc.identifier.urihttp://dx.doi.org/10.1109/SOSE.2019.00024
dc.identifier.urihttps://hdl.handle.net/10735.1/7840
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.rights©2019 IEEE
dc.source.journalIEEE International Conference on Service-Oriented System Engineering, 2019
dc.subjectCloud computing
dc.subjectInternet of things
dc.subjectSemantic computing
dc.subjectData mining
dc.subjectOntology
dc.subjectRobotics
dc.subjectSemantics
dc.subjectSpecifications
dc.subjectSystems engineering
dc.titleInvited Paper: Semantic IoT Data Description and Discovery in the IoT-Edge-Fog-Cloud Infrastructure
dc.type.genrearticle

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
JECS-7146-261144.32-LINK.pdf
Size:
165.48 KB
Format:
Adobe Portable Document Format
Description:
Link to Article