IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i9p2385-d168927.html
   My bibliography  Save this article

Solving Multi-Objective Fuzzy Optimization in Wireless Smart Sensor Networks under Uncertainty Using a Hybrid of IFR and SSO Algorithm

Author

Listed:
  • Meihua Wang

    (College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510633, China)

  • Wei-Chang Yeh

    (Integration and Collaboration Laboratory, Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 300, Taiwan)

  • Ta-Chung Chu

    (Department of Industrial Management and Information, Southern Taiwan University of Science and Technology, Tainan 700, Taiwan)

  • Xianyong Zhang

    (Department of Automation, Guangdong Polytechnic Normal University, Guangzhou 510633, China)

  • Chia-Ling Huang

    (Department of Logistics and Shipping Management, Kainan University, Taoyuan 33857, Taiwan)

  • Jun Yang

    (School of Mathematics, South China University of Technology, Guangzhou 510633, China)

Abstract

Wireless (smart) sensor networks (WSNs), networks made up of embedded wireless smart sensors, are an important paradigm with a wide range of applications, including the internet of things (IoT), smart grids, smart production systems, smart buildings and many others. WSNs achieve better execution efficiency if their energy consumption can be better controlled, because their component sensors are either difficult or impossible to recharge, and have a finite battery life. In addition, transmission cost must be minimized, and signal transmission quantity must be maximized to improve WSN performance. Thus, a multi-objective involving energy consumption, cost and signal transmission quantity in WSNs needs to be studied. Energy consumption, cost and signal transmission quantity usually have uncertain characteristics, and can often be represented by fuzzy numbers. Therefore, this work suggests a fuzzy simplified swarm optimization algorithm (fSSO) to resolve the multi-objective optimization problem consisting of energy consumption, cost and signal transmission quantity of the transmission process in WSNs under uncertainty. Finally, an experiment of ten benchmarks from smaller to larger scale WSNs is conducted to demonstrate the effectiveness and efficiency of the proposed fSSO algorithm.

Suggested Citation

  • Meihua Wang & Wei-Chang Yeh & Ta-Chung Chu & Xianyong Zhang & Chia-Ling Huang & Jun Yang, 2018. "Solving Multi-Objective Fuzzy Optimization in Wireless Smart Sensor Networks under Uncertainty Using a Hybrid of IFR and SSO Algorithm," Energies, MDPI, vol. 11(9), pages 1-23, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2385-:d:168927
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/9/2385/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/9/2385/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huang, Chia-Ling, 2015. "A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 221-230.
    2. Hisham A. Shehadeh & Mohd Yamani Idna Idris & Ismail Ahmedy & Roziana Ramli & Noorzaily Mohamed Noor, 2018. "The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications," Energies, MDPI, vol. 11(1), pages 1-35, January.
    3. Mohammad Tala’t & Chih-Min Yu & Meng-Lin Ku & Kai-Ten Feng, 2017. "On Hybrid Energy Utilization in Wireless Sensor Networks," Energies, MDPI, vol. 10(12), pages 1-11, November.
    4. Xianyong Zhang & Wei-chang Yeh & Yunzhi Jiang & Yaohong Huang & Yingwang Xiao & Li Li, 2018. "A Case Study of Control and Improved Simplified Swarm Optimization for Economic Dispatch of a Stand-Alone Modular Microgrid," Energies, MDPI, vol. 11(4), pages 1-21, March.
    5. Kosunalp, Selahattin, 2017. "An energy prediction algorithm for wind-powered wireless sensor networks with energy harvesting," Energy, Elsevier, vol. 139(C), pages 1275-1280.
    6. Lersteau, Charly & Rossi, André & Sevaux, Marc, 2018. "Minimum energy target tracking with coverage guarantee in wireless sensor networks," European Journal of Operational Research, Elsevier, vol. 265(3), pages 882-894.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yeh, Wei-Chang, 2021. "A quick BAT for evaluating the reliability of binary-state networks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. Yeh, Wei-Chang, 2020. "A new method for verifying d-MC candidates," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    3. Wei-Chang Yeh & Yu-Hsin Hsieh & Chia-Ling Huang, 2022. "Newly Developed Flexible Grid Trading Model Combined ANN and SSO algorithm," Papers 2211.12839, arXiv.org.
    4. Hao, Zhifeng & Yeh, Wei-Chang & Zuo, Ming & Wang, Jing, 2020. "Multi-distribution multi-commodity multistate flow network model and its reliability evaluation algorithm," Reliability Engineering and System Safety, Elsevier, vol. 193(C).

    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. Yeh, Wei-Chang & Zhu, Wenbo & Tan, Shi-Yi & Wang, Gai-Ge & Yeh, Yuan-Hui, 2022. "Novel general active reliability redundancy allocation problems and algorithm," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    2. Zaretalab, Arash & Sharifi, Mani & Guilani, Pedram Pourkarim & Taghipour, Sharareh & Niaki, Seyed Taghi Akhavan, 2022. "A multi-objective model for optimizing the redundancy allocation, component supplier selection, and reliable activities for multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    3. Amirhossain Chambari & Javad Sadeghi & Fakhri Bakhtiari & Reza Jahangard, 2016. "A note on a reliability redundancy allocation problem using a tuned parameter genetic algorithm," OPSEARCH, Springer;Operational Research Society of India, vol. 53(2), pages 426-442, June.
    4. Li, Shuai & Chi, Xuefen & Yu, Baozhu, 2022. "An improved particle swarm optimization algorithm for the reliability–redundancy allocation problem with global reliability," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    5. Yeh, Wei-Chang & Chu, Ta-Chung, 2018. "A novel multi-distribution multi-state flow network and its reliability optimization problem," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 209-217.
    6. Ouyang, Zhiyuan & Liu, Yu & Ruan, Sheng-Jia & Jiang, Tao, 2019. "An improved particle swarm optimization algorithm for reliability-redundancy allocation problem with mixed redundancy strategy and heterogeneous components," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 62-74.
    7. Wang, Junlei & Tang, Lihua & Zhao, Liya & Zhang, Zhien, 2019. "Efficiency investigation on energy harvesting from airflows in HVAC system based on galloping of isosceles triangle sectioned bluff bodies," Energy, Elsevier, vol. 172(C), pages 1066-1078.
    8. Yeh, Wei-Chang, 2023. "QB-II for evaluating the reliability of binary-state networks," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    9. Yeh, Wei-Chang & He, Min-Fan & Huang, Chia-Ling & Tan, Shi-Yi & Zhang, Xianyong & Huang, Yaohong & Li, Li, 2020. "New genetic algorithm for economic dispatch of stand-alone three-modular microgrid in DongAo Island," Applied Energy, Elsevier, vol. 263(C).
    10. Calvete, Herminia I. & del-Pozo, Lourdes & Iranzo, José A., 2018. "Dealing with residual energy when transmitting data in energy-constrained capacitated networks," European Journal of Operational Research, Elsevier, vol. 269(2), pages 602-620.
    11. Soheil Azizi & Milad Mohammadi, 2023. "Strategy selection for multi-objective redundancy allocation problem in a k-out-of-n system considering the mean time to failure," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 1021-1044, June.
    12. Wei-Chang Yeh & Yunzhi Jiang & Yee-Fen Chen & Zhe Chen, 2016. "A New Soft Computing Method for K-Harmonic Means Clustering," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-14, November.
    13. Ridhi Kapoor & Sandeep Sharma, 2023. "Glowworm Swarm Optimization (GSO) based energy efficient clustered target coverage routing in Wireless Sensor Networks (WSNs)," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(2), pages 622-634, May.
    14. Paweł Dymora & Mirosław Mazurek & Krzysztof Smalara, 2021. "Modeling and Fault Tolerance Analysis of ZigBee Protocol in IoT Networks," Energies, MDPI, vol. 14(24), pages 1-21, December.
    15. Nath, Rahul & Muhuri, Pranab K., 2022. "Evolutionary Optimization based Solution approaches for Many Objective Reliability-Redundancy Allocation Problem," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    16. Xianyong Zhang & Yaohong Huang & Li Li & Wei-Chang Yeh, 2018. "Power and Capacity Consensus Tracking of Distributed Battery Storage Systems in Modular Microgrids," Energies, MDPI, vol. 11(6), pages 1-25, June.
    17. Huang, Xianzhen & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2019. "A heuristic survival signature based approach for reliability-redundancy allocation," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 511-517.
    18. Yeh, Wei-Chang, 2022. "Novel direct algorithm for computing simultaneous all-level reliability of multistate flow networks," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    19. Yeh, Wei-Chang, 2021. "A quick BAT for evaluating the reliability of binary-state networks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    20. Peng, Yongbo & Ma, Yangying & Huang, Tianchen & De Domenico, Dario, 2021. "Reliability-based design optimization of adaptive sliding base isolation system for improving seismic performance of structures," Reliability Engineering and System Safety, Elsevier, vol. 205(C).

    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:jeners:v:11:y:2018:i:9:p:2385-:d:168927. 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.