An Open Geospatial Internet of Things Cloud Service Architecture Based on the Big Data Lambda Architecture
| dc.contributor.advisor | Liang, Steve H. L. | |
| dc.contributor.author | Khalafbeigi, Tania | |
| dc.contributor.committeemember | Wang, Xin | |
| dc.contributor.committeemember | Wang, Mea | |
| dc.contributor.committeemember | Li, Wenwen | |
| dc.contributor.committeemember | Elhajj, Reda | |
| dc.date | 2019-02 | |
| dc.date.accessioned | 2019-01-03T16:07:40Z | |
| dc.date.available | 2019-01-03T16:07:40Z | |
| dc.date.issued | 2018-12-20 | |
| dc.description.abstract | The Internet of Things (IoT) consists of sensors and actuators embedded in everyday devices interconnecting and communicating through interoperable information and communication technologies. The real potential of IoT is in creating innovative applications by integrating and repurposing IoT sensing and controlling capabilities from different sources. However, proprietary IoT systems now create silos that make the IoT goal almost unreachable as the applications need to deal with heterogeneous data from different systems. In addition to the problem of heterogeneity, big data is a challenge for all technologies in the modern world. As predicted by CISCO and IDC, the number of internet-connected objects will reach at least 50 billion by 2020. As a result, IoT is facing heterogeneity and big data challenges including volume and velocity. We have proposed an architecture for IoT with the focus on data management challenges in this dissertation. The proposed architecture merges the Lambda architecture with the SensorThings API. The SensorThings API is used as a solution for the heterogeneity problem. One of the solutions for data heterogeneity or so-called interoperability in IoT is the use of a standard API. SensorThings API has been proven to be a mature, open geospatial standard for IoT by various literature, implementations, and its widespread adoption. Moreover, the Lambda architecture addresses big data volume and velocity challenges through the use of three layers architecture: batch, serving, and speed. We implemented a case study of our proposed architecture with real air quality data. For our implementation, we used Hadoop and Azure technologies. Our case study showed that our proposed architecture significantly improves the performance of IoT service on real-world big open data. | en_US |
| dc.identifier.citation | Khalafbeigi, T. (2018). An Open Geospatial Internet of Things Cloud Service Architecture Based on the Big Data Lambda Architecture (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. | en_US |
| dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/35673 | |
| dc.identifier.uri | http://hdl.handle.net/1880/109398 | |
| dc.language.iso | en | en_US |
| dc.publisher.faculty | Schulich School of Engineering | en_US |
| dc.publisher.institution | University of Calgary | en |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | en_US |
| dc.subject | Internet of Things | en_US |
| dc.subject | Big Data | en_US |
| dc.subject | OGC SensorThings API | en_US |
| dc.subject | Lambda Architecture | en_US |
| dc.subject.classification | Computer Science | en_US |
| dc.title | An Open Geospatial Internet of Things Cloud Service Architecture Based on the Big Data Lambda Architecture | en_US |
| dc.type | doctoral thesis | en_US |
| thesis.degree.discipline | Engineering – Geomatics | en_US |
| thesis.degree.grantor | University of Calgary | en_US |
| thesis.degree.name | Doctor of Philosophy (PhD) | en_US |
| ucalgary.item.requestcopy | true |