research-article

Context-Driven and Real-Time Provisioning of Data-Centric IoT Services in the Cloud

Authors:

Amir Taherkordi,

Frank Eliassen,

Michael Mcdonald,

Geir HornAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 19, Issue 1

Article No.: 7, Pages 1 - 24

https://doi.org/10.1145/3151006

Published: 30 November 2018 Publication History

Abstract

The convergence of Internet of Things (IoT) and the Cloud has significantly facilitated the provision and management of services in large-scale applications, such as smart cities. With a huge number of IoT services accessible through clouds, it is very important to model and expose cloud-based IoT services in an efficient manner, promising easy and real-time delivery of cloud-based, data-centric IoT services. The existing work in this area has adopted a uniform and flat view to IoT services and their data, making it difficult to achieve the above goal. In this article, we propose a software framework, Context-driven And Real-time IoT (CARIoT) for real-time provisioning of cloud-based IoT services and their data, driven by their contextual properties. The main idea behind the proposed framework is to structure the description of data-centric IoT services and their real-time and historical data in a hierarchical form in accordance with the end-user application’s context model. CARIoT features design choices and software services to realize this service provisioning model and the supporting data structures for hierarchical IoT data access. Using this approach, end-user applications can access IoT services and subscribe to their real-time and historical data in an efficient manner at different contextual levels, e.g., from a municipal district to a street in smart city use cases. We leverage a popular cloud-based data storage platform, called Firebase, to implement the CARIoT framework and evaluate its efficiency. The evaluation results show that CARIoT’s hierarchical structure imposes no additional overhead with less data notification delay as compared to existing flat structures.

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Cited By

Girau RAnedda MPresta RCorpino SRuiu PFadda MLam CGiusto D(2024)Definition and implementation of the Cloud Infrastructure for the integration of the Human Digital Twin in the Social Internet of ThingsComputer Networks10.1016/j.comnet.2024.110632251(110632)Online publication date: Sep-2024
https://doi.org/10.1016/j.comnet.2024.110632
Tian ZZhang CXiao JLiang S(2023)A Graph-Based Service Composition Method for Science and Technology ResourcesHuman Centered Computing10.1007/978-3-031-23741-6_23(252-258)Online publication date: 1-Jan-2023
https://doi.org/10.1007/978-3-031-23741-6_23
Shahraki AAbbasi MTaherkordi AJurcut A(2022)Active Learning for Network Traffic Classification: A Technical StudyIEEE Transactions on Cognitive Communications and Networking10.1109/TCCN.2021.31190628:1(422-439)Online publication date: Mar-2022
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Index Terms

Context-Driven and Real-Time Provisioning of Data-Centric IoT Services in the Cloud
1. Applied computing
  1. Life and medical sciences
    1. Health informatics
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Software system models

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Published In

cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 19, Issue 1

Regular Papers, Special Issue on Service Management for IOT and Special Issue on Knowledge-Driven BPM

February 2019

321 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/3283809

Editor:
Ling Liu
Georgia Institute of Technology, USA

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Copyright © 2018 ACM.

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 November 2018

Accepted: 01 October 2017

Revised: 01 August 2017

Received: 01 March 2017

Published in TOIT Volume 19, Issue 1

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Cited By

Girau RAnedda MPresta RCorpino SRuiu PFadda MLam CGiusto D(2024)Definition and implementation of the Cloud Infrastructure for the integration of the Human Digital Twin in the Social Internet of ThingsComputer Networks10.1016/j.comnet.2024.110632251(110632)Online publication date: Sep-2024
https://doi.org/10.1016/j.comnet.2024.110632
Tian ZZhang CXiao JLiang S(2023)A Graph-Based Service Composition Method for Science and Technology ResourcesHuman Centered Computing10.1007/978-3-031-23741-6_23(252-258)Online publication date: 1-Jan-2023
https://doi.org/10.1007/978-3-031-23741-6_23
Shahraki AAbbasi MTaherkordi AJurcut A(2022)Active Learning for Network Traffic Classification: A Technical StudyIEEE Transactions on Cognitive Communications and Networking10.1109/TCCN.2021.31190628:1(422-439)Online publication date: Mar-2022
https://doi.org/10.1109/TCCN.2021.3119062
Chen CHelal AJin ZZhang MLee C(2021)IoTranx: Transactions for Safer Smart SpacesACM Transactions on Cyber-Physical Systems10.1145/34719376:1(1-26)Online publication date: 23-Nov-2021
https://dl.acm.org/doi/10.1145/3471937
Wan LZhang MSun LWang X(2021)Machine Learning Empowered IoT for Intelligent Vehicle Location in Smart CitiesACM Transactions on Internet Technology10.1145/344861221:3(1-25)Online publication date: 10-Aug-2021
https://dl.acm.org/doi/10.1145/3448612
Esmaeilyfard RNaderi M(2021)Distributed composition of complex event services in IoT networkThe Journal of Supercomputing10.1007/s11227-020-03498-277:6(6123-6144)Online publication date: 1-Jun-2021
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Luckner MGrzenda MKunicki RLegierski J(2020)IoT Architecture for Urban Data-Centric Services and ApplicationsACM Transactions on Internet Technology10.1145/339685020:3(1-30)Online publication date: 24-Jul-2020
https://dl.acm.org/doi/10.1145/3396850
Huang HGuo S(2020)Data-Driven Service ProvisioningEncyclopedia of Wireless Networks10.1007/978-3-319-78262-1_93(308-312)Online publication date: 30-Aug-2020
https://doi.org/10.1007/978-3-319-78262-1_93
Shooshtarian LLan DTaherkordi A(2019)A Clustering-Based Approach to Efficient Resource Allocation in Fog ComputingPervasive Systems, Algorithms and Networks10.1007/978-3-030-30143-9_17(207-224)Online publication date: 27-Nov-2019
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Huang HGuo S(2018)Data-Driven Service ProvisioningEncyclopedia of Wireless Networks10.1007/978-3-319-32903-1_93-1(1-5)Online publication date: 14-Dec-2018
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