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IoT Mashups: From IoT Big Data to IoT Big Service

Published: 19 July 2017 Publication History

Abstract

Internet of Things (IoT) addresses the challenge to provide a transparent access to a huge number of IoT resources that can be either physical devices or just data resources. Moreover, because of the large number of resource-constrained devices and the dynamic nature of IoT environments, integrating the resulted data becomes a non trivial task. We believe that the use of mashups, a way to compose new services from existing ones, can be a solution to the above challenge if each resource exposes its functionalities as a Web service. In the IoT environment, this will constitute a Web of Things where mashups development will take advantage of the connected physical world. The huge amounts of IoT-generated data from physical devices and data sources, called IoT Big Data, requires new design solutions to speed up data processing, scale up with the data volume and improve data adaptability. Besides existing techniques for IoT data collection, filtering, and analytics, we present in this article a mashup oriented model, called IoT Big Services, for provisioning data-centric IoT services in the context of IOT mashups. These IoT services are organized in tree structure where each node, called an IoT Big Service, acts as an integrator that collects data from lower level, processes them and delivers the results to higher level in the architecture.

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Cited By

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  • (2023)On the use of big data frameworks in big service managementJournal of Software: Evolution and Process10.1002/smr.2642Online publication date: Dec-2023
  • (2022)A Conversational Approach for Modifying Service Mashups in IoT EnvironmentsProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517655(1-16)Online publication date: 29-Apr-2022
  • (2021)A Service-Oriented Approach for Sensing in the Internet of Things: Intelligent Transportation Systems and Privacy Use CasesIEEE Sensors Journal10.1109/JSEN.2020.298155821:14(15753-15761)Online publication date: 15-Jul-2021
  • Show More Cited By

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cover image ACM Other conferences
ICFNDS '17: Proceedings of the International Conference on Future Networks and Distributed Systems
July 2017
325 pages
ISBN:9781450348447
DOI:10.1145/3102304
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 19 July 2017

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Author Tags

  1. Big Data
  2. Big Services
  3. Internet of Things
  4. Mashup application

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Cited By

View all
  • (2023)On the use of big data frameworks in big service managementJournal of Software: Evolution and Process10.1002/smr.2642Online publication date: Dec-2023
  • (2022)A Conversational Approach for Modifying Service Mashups in IoT EnvironmentsProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517655(1-16)Online publication date: 29-Apr-2022
  • (2021)A Service-Oriented Approach for Sensing in the Internet of Things: Intelligent Transportation Systems and Privacy Use CasesIEEE Sensors Journal10.1109/JSEN.2020.298155821:14(15753-15761)Online publication date: 15-Jul-2021
  • (2021)Heralding the Future of Federated Learning Framework: Architecture, Tools and Future Directions2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence)10.1109/Confluence51648.2021.9377066(698-703)Online publication date: 28-Jan-2021
  • (2021)Optimized Composition for Multiple User Service Requests Based on Edge-Cloud CollaborationIEEE Access10.1109/ACCESS.2021.30939369(94862-94878)Online publication date: 2021
  • (2021)Multitier Intelligent Computing and Storage for IoT Sensor DataHandbook of Smart Cities10.1007/978-3-030-69698-6_49(929-955)Online publication date: 10-Jul-2021
  • (2021)Multitier Intelligent Computing and Storage for IoT Sensor DataHandbook of Smart Cities10.1007/978-3-030-15145-4_49-1(1-28)Online publication date: 28-Mar-2021
  • (2019)Survey of IoT platforms supporting artificial intelligenceProceedings of the Conference on Research in Adaptive and Convergent Systems10.1145/3338840.3355694(65-66)Online publication date: 24-Sep-2019

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