research-article

Fuzzy logic and MCDA in IoT resources classification

Authors:

Mauricio Pilla,

Ana Marilza Pernas,

Adenauer YaminAuthors Info & Claims

SAC '18: Proceedings of the 33rd Annual ACM Symposium on Applied Computing

Pages 761 - 766

https://doi.org/10.1145/3167132.3167216

Published: 09 April 2018 Publication History

Abstract

Internet of Things is characterized by a lot of resources connected to the Internet, many simultaneously requesting and providing services. The adequate selection of resources that best meets the demands of users with a broad range of options has been a relevant and current research challenge. Based on the non-functional parameters of QoS, it plays a significant role in the ranking of these resources according to the services they offer. This work presents a proposal to classify and select the most appropriate resource to the client's request, using fuzzy logic to treat uncertainties in the definition of ideal weights for QoS attributes. It also proposes to add fuzzy logic in the pre-classification of resources, to reduce the computational cost generated by MCDA algorithms. The accuracy of the proposed model in the pre-classification of the best resources is presented, and the results obtained are promising and indicate the continuity of the research.

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Cited By

Małysiak-Mrozek BRyba BMolęda MHung CPedrycz WDing WMrozek D(2024)Interpreting Industrial IoT Data Streams Through Fuzzy Querying With Hysteretic Fuzzy Sets on Apache KafkaIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.340958532:8(4671-4684)Online publication date: Aug-2024
https://doi.org/10.1109/TFUZZ.2024.3409585
Sekh INehéz K(2024)Intelligent SLA Selection Through the Validation Cloud Broker SystemIEEE Access10.1109/ACCESS.2024.343961712(110230-110247)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3439617
Małysiak-Mrozek BBas MSunderam VKozielski SMrozek D(2023)Predicting Conflict Zones on Terrestrial Routes of Automated Guided Vehicles with Fuzzy Querying on Apache Kafka2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA60987.2023.10302592(1-8)Online publication date: 9-Oct-2023
https://doi.org/10.1109/DSAA60987.2023.10302592
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Index Terms

Fuzzy logic and MCDA in IoT resources classification
1. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Software infrastructure
        Middleware

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Published In

cover image ACM Conferences

SAC '18: Proceedings of the 33rd Annual ACM Symposium on Applied Computing

April 2018

2327 pages

ISBN:9781450351911

DOI:10.1145/3167132

Conference Chairs:
Hisham M. Haddad
Kennesaw State University
,
Roger L. Wainwright
University of Tulsa
,
Richard Chbeir
University of Pau & Pays Adour, France

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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SIGAPP: ACM Special Interest Group on Applied Computing

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New York, NY, United States

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Published: 09 April 2018

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SAC 2018

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SAC 2018: Symposium on Applied Computing

April 9 - 13, 2018

Pau, France

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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SAC '25

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The 40th ACM/SIGAPP Symposium on Applied Computing

March 31 - April 4, 2025

Catania , Italy

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Cited By

Małysiak-Mrozek BRyba BMolęda MHung CPedrycz WDing WMrozek D(2024)Interpreting Industrial IoT Data Streams Through Fuzzy Querying With Hysteretic Fuzzy Sets on Apache KafkaIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.340958532:8(4671-4684)Online publication date: Aug-2024
https://doi.org/10.1109/TFUZZ.2024.3409585
Sekh INehéz K(2024)Intelligent SLA Selection Through the Validation Cloud Broker SystemIEEE Access10.1109/ACCESS.2024.343961712(110230-110247)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3439617
Małysiak-Mrozek BBas MSunderam VKozielski SMrozek D(2023)Predicting Conflict Zones on Terrestrial Routes of Automated Guided Vehicles with Fuzzy Querying on Apache Kafka2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA60987.2023.10302592(1-8)Online publication date: 9-Oct-2023
https://doi.org/10.1109/DSAA60987.2023.10302592
Zayat WKilic HYalcin AZaim SDelen D(2023)Application of MADM methods in Industry 4.0: A literature reviewComputers & Industrial Engineering10.1016/j.cie.2023.109075177(109075)Online publication date: Mar-2023
https://doi.org/10.1016/j.cie.2023.109075
Costa FNassar SDantas M(2023)A Sensor Ranking Approach for Edge–Fog–Cloud EnvironmentsSN Computer Science10.1007/s42979-023-01826-w4:4Online publication date: 13-May-2023
https://dl.acm.org/doi/10.1007/s42979-023-01826-w
Lindner JEberle UKnuepffer ECoelho C(2021)Moving beyond land use intensity types: assessing biodiversity impacts using fuzzy thinkingThe International Journal of Life Cycle Assessment10.1007/s11367-021-01899-wOnline publication date: 5-Jul-2021
https://doi.org/10.1007/s11367-021-01899-w
Mrozek DTokarz KPankowski DMalysiak-Mrozek B(2020)A Hopping Umbrella for Fuzzy Joining Data Streams From IoT Devices in the Cloud and on the EdgeIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2019.295505628:5(916-928)Online publication date: May-2020
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de Moura RSchneider Gde Souza Oliveira LPilla MYamin AReiser R(2020)f-HybridMem: A Fuzzy-based Approach for Decision Support in Hybrid Memory Management2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)10.1109/FUZZ48607.2020.9177585(1-8)Online publication date: Jul-2020
https://doi.org/10.1109/FUZZ48607.2020.9177585
Pattar SCR SVala DChouhan DBuyya RKR VIyengar SPatnaik L(2020)Context-Oriented User-Centric Search System for the IoT Based on Fuzzy ClusteringAdvances in Computational Intelligence, Security and Internet of Things10.1007/978-981-15-3666-3_28(343-356)Online publication date: 5-Mar-2020
https://doi.org/10.1007/978-981-15-3666-3_28
Mrozek DMilik MMałysiak-Mrozek BTokarz KDuszenko AKozielski S(2020)Fuzzy Intelligence in Monitoring Older Adults with WearablesComputational Science – ICCS 202010.1007/978-3-030-50426-7_22(288-301)Online publication date: 15-Jun-2020
https://doi.org/10.1007/978-3-030-50426-7_22

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