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Article

Hadoop Oriented Smart Cities Architecture

Department of Computer Science and Cybernetics, Bucharest University of Economic Studies, Bucharest 010374, Romania
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Author to whom correspondence should be addressed.
Sensors 2018, 18(4), 1181; https://doi.org/10.3390/s18041181
Submission received: 12 March 2018 / Revised: 6 April 2018 / Accepted: 10 April 2018 / Published: 12 April 2018
(This article belongs to the Section Sensor Networks)

Abstract

A smart city implies a consistent use of technology for the benefit of the community. As the city develops over time, components and subsystems such as smart grids, smart water management, smart traffic and transportation systems, smart waste management systems, smart security systems, or e-governance are added. These components ingest and generate a multitude of structured, semi-structured or unstructured data that may be processed using a variety of algorithms in batches, micro batches or in real-time. The ICT architecture must be able to handle the increased storage and processing needs. When vertical scaling is no longer a viable solution, Hadoop can offer efficient linear horizontal scaling, solving storage, processing, and data analyses problems in many ways. This enables architects and developers to choose a stack according to their needs and skill-levels. In this paper, we propose a Hadoop-based architectural stack that can provide the ICT backbone for efficiently managing a smart city. On the one hand, Hadoop, together with Spark and the plethora of NoSQL databases and accompanying Apache projects, is a mature ecosystem. This is one of the reasons why it is an attractive option for a Smart City architecture. On the other hand, it is also very dynamic; things can change very quickly, and many new frameworks, products and options continue to emerge as others decline. To construct an optimized, modern architecture, we discuss and compare various products and engines based on a process that takes into consideration how the products perform and scale, as well as the reusability of the code, innovations, features, and support and interest in online communities.
Keywords: smart cities; sensors; Hadoop; Spark; Elasticsearch; cloud computing; IoT smart cities; sensors; Hadoop; Spark; Elasticsearch; cloud computing; IoT

Share and Cite

MDPI and ACS Style

Diaconita, V.; Bologa, A.-R.; Bologa, R. Hadoop Oriented Smart Cities Architecture. Sensors 2018, 18, 1181. https://doi.org/10.3390/s18041181

AMA Style

Diaconita V, Bologa A-R, Bologa R. Hadoop Oriented Smart Cities Architecture. Sensors. 2018; 18(4):1181. https://doi.org/10.3390/s18041181

Chicago/Turabian Style

Diaconita, Vlad, Ana-Ramona Bologa, and Razvan Bologa. 2018. "Hadoop Oriented Smart Cities Architecture" Sensors 18, no. 4: 1181. https://doi.org/10.3390/s18041181

APA Style

Diaconita, V., Bologa, A.-R., & Bologa, R. (2018). Hadoop Oriented Smart Cities Architecture. Sensors, 18(4), 1181. https://doi.org/10.3390/s18041181

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