A Heterogeneous Approach for Developing Applications with FIWARE GEs

Cola, Simone Di; Tran, Cuong; Lau, Kung-Kiu; Celesti, Antonio; Fazio, Maria

doi:10.1007/978-3-319-24072-5_5

Cited by 7 publications

(3 citation statements)

References 14 publications

(14 reference statements)

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“…The SmartPort project is born from a collaboration agreement between the University of Las Palmas de Gran Canaria (ULPGC), Las Palmas de Gran Canaria Port Authority and the FIWARE program. FIWARE is an open project sponsored by the Future Internet Public Private Partnership (FI-PPP) program, created by the European Commission [ 6 ]. It enables the validation of new concepts and technologies, as well as new business models and applications.…”

Section: Introductionmentioning

confidence: 99%

SmartPort: A Platform for Sensor Data Monitoring in a Seaport Based on FIWARE

Fernández

Santana

Ortega

et al. 2016

Sensors

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Seaport monitoring and management is a significant research area, in which infrastructure automatically collects big data sets that lead the organization in its multiple activities. Thus, this problem is heavily related to the fields of data acquisition, transfer, storage, big data analysis and information visualization. Las Palmas de Gran Canaria port is a good example of how a seaport generates big data volumes through a network of sensors. They are placed on meteorological stations and maritime buoys, registering environmental parameters. Likewise, the Automatic Identification System (AIS) registers several dynamic parameters about the tracked vessels. However, such an amount of data is useless without a system that enables a meaningful visualization and helps make decisions. In this work, we present SmartPort, a platform that offers a distributed architecture for the collection of the port sensors’ data and a rich Internet application that allows the user to explore the geolocated data. The presented SmartPort tool is a representative, promising and inspiring approach to manage and develop a smart system. It covers a demanding need for big data analysis and visualization utilities for managing complex infrastructures, such as a seaport.

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Section: Introductionmentioning

confidence: 99%

SmartPort: A Platform for Sensor Data Monitoring in a Seaport Based on FIWARE

Fernández

Santana

Ortega

et al. 2016

Sensors

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“…-OpenStack 17 : implements the Cloud IaaS GE that provides the facilities to provision virtual machines, as well as to associated compute, storage and network resources -Murano 18 : implements the Application Management GE that provides a ready-to-use catalogue of applications that can be deployed in a OpenStack 19 cloud infrastructure While some components have been developed within the context of the project, other consolidated open source projects have been adopted as the reference implementation for some GEs, such as Open Stack, CKAN 20 , and Docker 21 . There are some previously work in the literature that exploited FIWARE GEs components in various domains (Cola et al, 2015;Salhofer, 2018;Steinmetz et al, 2017;Bellabas et al, 2013). These works usually combine a small set of GEs to provide the basis for the development of different prototype applications for end users.…”

Section: Fiwarementioning

confidence: 99%

“…Although the division of categories helps in understanding the architecture proposed by FIWARE, a large number of options to compose an instance of the platform and the overlapping of existing functionalities among several components make its architecture extraordinarily complex. In addition, although the community provides Docker images for each of the components to facilitate their deployment and running environment, there is a considerable manual effort required to compose them (Cola et al, 2015). Besides, several implementations of FIWARE GE are deprecated, and there are no alternatives provided by the project community.…”

Section: Fiwarementioning

confidence: 99%

A scalable microservice-based open source platform for smart cities

Esposte¹

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One Tree Hill-U2 ical teachings which I used extensively during this thesis. I acknowledge my advisor, Professor Fabio Kon, for the opportunity to do this Master's degree, and for his support and guidance along this thesis. He has given me many opportunities of growth, learning, living, and working, that impacted significantly on my academic education. I acknowledge Professor Fabio Costa, Professor Kelly Braghetto, and Nelson Lago for their excellent contributions to the experiments carried out during this thesis and for co-authoring the papers that were published for the dissemination of the results obtained. We acknowledge Lucas Kanashiro and Eduardo Santana for their contributions in the final experiments of the platform, mainly in the integration of the platform with the simulator and in the definition of the used scenario. We also acknowledge the following developers for their contributions to the InterSCity platform source code:

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