IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v14y2022i10p281-d929101.html
   My bibliography  Save this article

Improving Quality Indicators of the Cloud-Based IoT Networks Using an Improved Form of Seagull Optimization Algorithm

Author

Listed:
  • Hamza Mohammed Ridha Al-Khafaji

    (Biomedical Engineering Department, Al-Mustaqbal University College, Hillah 51001, Babil, Iraq)

Abstract

The Internet of things (IoT) points to billions of devices located worldwide which are connected and share their data based on the Internet. Due to the new technologies that provide cheap computer chips and universal wireless networks, it is feasible that everything from a small tablet to a very large airplane will be connected to the Internet and will be a part of the IoT. In most applications, IoT network nodes face limitations in terms of energy source and cost. Therefore, the need for innovative methods to improve quality indicators that increase the lifespan of networks is evident. Here, a novel technique is presented to increase the quality of service (QoS) in IoT using an improved meta-heuristic algorithm, called the improved seagull optimization algorithm (ISOA), along with traffic management in these networks. Based on this subject, the traffic-aware algorithm can manage the sending of packets and increase the QoS provision in terms of time to a great extent. The performance evaluation of the proposed method and comparison with the previous methods demonstrated the accuracy and efficiency of this method and its superiority over the previous works.

Suggested Citation

  • Hamza Mohammed Ridha Al-Khafaji, 2022. "Improving Quality Indicators of the Cloud-Based IoT Networks Using an Improved Form of Seagull Optimization Algorithm," Future Internet, MDPI, vol. 14(10), pages 1-13, September.
    • Handle: RePEc:gam:jftint:v:14:y:2022:i:10:p:281-:d:929101
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/14/10/281/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/14/10/281/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ali Alferaidi & Kusum Yadav & Yasser Alharbi & Navid Razmjooy & Wattana Viriyasitavat & Kamal Gulati & Sandeep Kautish & Gaurav Dhiman & Ramin Ranjbarzadeh, 2022. "Distributed Deep CNN-LSTM Model for Intrusion Detection Method in IoT-Based Vehicles," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, March.
    2. Yang, Dixiong & Li, Gang & Cheng, Gengdong, 2007. "On the efficiency of chaos optimization algorithms for global optimization," Chaos, Solitons & Fractals, Elsevier, vol. 34(4), pages 1366-1375.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maytham N. Meqdad & Seifedine Kadry & Hafiz Tayyab Rauf, 2022. "Improved Dragonfly Optimization Algorithm for Detecting IoT Outlier Sensors," Future Internet, MDPI, vol. 14(10), pages 1-16, October.
    2. Sun, Yeong-Jeu, 2009. "An exponential observer for the generalized Rossler chaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2457-2461.
    3. Cui, Yunfei & Geng, Zhiqiang & Zhu, Qunxiong & Han, Yongming, 2017. "Review: Multi-objective optimization methods and application in energy saving," Energy, Elsevier, vol. 125(C), pages 681-704.
    4. Wei-Chiang Hong & Yucheng Dong & Chien-Yuan Lai & Li-Yueh Chen & Shih-Yung Wei, 2011. "SVR with Hybrid Chaotic Immune Algorithm for Seasonal Load Demand Forecasting," Energies, MDPI, vol. 4(6), pages 1-18, June.
    5. Imene Khenissi & Tawfik Guesmi & Ismail Marouani & Badr M. Alshammari & Khalid Alqunun & Saleh Albadran & Salem Rahmani & Rafik Neji, 2023. "Energy Management Strategy for Optimal Sizing and Siting of PVDG-BES Systems under Fixed and Intermittent Load Consumption Profile," Sustainability, MDPI, vol. 15(2), pages 1-28, January.
    6. Coelho, Leandro dos Santos, 2009. "Reliability–redundancy optimization by means of a chaotic differential evolution approach," Chaos, Solitons & Fractals, Elsevier, vol. 41(2), pages 594-602.
    7. Salil Bharany & Sandeep Sharma & Surbhi Bhatia & Mohammad Khalid Imam Rahmani & Mohammed Shuaib & Saima Anwar Lashari, 2022. "Energy Efficient Clustering Protocol for FANETS Using Moth Flame Optimization," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    8. Sultan Almotairi & Elsayed Badr & Mustafa Abdul Salam & Alshimaa Dawood, 2023. "Three Chaotic Strategies for Enhancing the Self-Adaptive Harris Hawk Optimization Algorithm for Global Optimization," Mathematics, MDPI, vol. 11(19), pages 1-27, October.
    9. Cheng, Shen & Zhao, Gaiju & Gao, Ming & Shi, Yuetao & Huang, Mingming & Yousefi, Nasser, 2021. "Optimal hybrid energy system for locomotive utilizing improved Locust Swarm optimizer," Energy, Elsevier, vol. 218(C).
    10. Wu, Cong & Li, Jiaxuan & Liu, Wenjin & He, Yuzhe & Nourmohammadi, Samad, 2023. "Short-term electricity demand forecasting using a hybrid ANFIS–ELM network optimised by an improved parasitism–predation algorithm," Applied Energy, Elsevier, vol. 345(C).
    11. Martin Ćalasan & Dražen Jovanović & Vesna Rubežić & Saša Mujović & Slobodan Đukanović, 2019. "Estimation of Single-Diode and Two-Diode Solar Cell Parameters by Using a Chaotic Optimization Approach," Energies, MDPI, vol. 12(21), pages 1-14, November.
    12. El-Shorbagy, M.A. & Mousa, A.A. & Nasr, S.M., 2016. "A chaos-based evolutionary algorithm for general nonlinear programming problems," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 8-21.
    13. Hossein Lotfi, 2022. "A Multiobjective Evolutionary Approach for Solving the Multi-Area Dynamic Economic Emission Dispatch Problem Considering Reliability Concerns," Sustainability, MDPI, vol. 15(1), pages 1-23, December.
    14. Rani, Mamta & Agarwal, Rashi, 2009. "A new experimental approach to study the stability of logistic map," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 2062-2066.
    15. Naanaa, Anis, 2015. "Fast chaotic optimization algorithm based on spatiotemporal maps for global optimization," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 402-411.
    16. Li, Huan & Li, Kun & Zafetti, Nicholas & Gu, Jianfeng, 2020. "Improvement of energy supply configuration for telecommunication system in remote area s based on improved chaotic world cup optimization algorithm," Energy, Elsevier, vol. 192(C).
    17. Rani, Mamta & Agarwal, Rashi, 2009. "Generation of fractals from complex logistic map," Chaos, Solitons & Fractals, Elsevier, vol. 42(1), pages 447-452.
    18. Deepak Kumar & Mamta Rani, 2022. "Alternated Superior Chaotic Biogeography-Based Algorithm for Optimization Problems," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 13(1), pages 1-39, January.
    19. He, Yao-Yao & Zhou, Jian-Zhong & Xiang, Xiu-Qiao & Chen, Heng & Qin, Hui, 2009. "Comparison of different chaotic maps in particle swarm optimization algorithm for long-term cascaded hydroelectric system scheduling," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 3169-3176.
    20. He, Bohao & Jia, Biying & Zhao, Yanghe & Wang, Xu & Wei, Mao & Dietzel, Ranae, 2022. "Estimate soil moisture of maize by combining support vector machine and chaotic whale optimization algorithm," Agricultural Water Management, Elsevier, vol. 267(C).

    More about this item

    Keywords

    IoT; ISOA; QoS; quality indicators;
    All these keywords.

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:14:y:2022:i:10:p:281-:d:929101. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.