International Journal of Wireless and Ad Hoc Communication

Journal DOI

https://doi.org/10.54216/IJWAC

Submit Your Paper

2692-4056ISSN (Online)

Volume 4 , Issue 2 , PP: 97-106, 2022 | Cite this article as | XML | Html | PDF | Full Length Article

Modified Flower Pollination Algorithm based Resource Management Model for Clustered IoT Network

Tarek Gaber 1 * , Chin-Shiuh Shieh 2 , Yuh-Chung Lin 3 , Fatma Masmoudi 4

  • 1 School of Science, Engineering & Environment, University of Salford, UK - (tmgaber@gmail.com)
  • 2 Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 807618, Taiwan - (csshieh@nkust.edu.tw)
  • 3 School of Information Science and Technology, Sanda University, Shanghai 201029, China - (yuhchung@sandau.edu.cn)
  • 4 College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Alkharj, 11942, Saudi Arabia - (f.masmoudi@psau.edu.sa)
  • Doi: https://doi.org/10.54216/IJWAC.040205

    Received: March 27, 2022 Accepted: August 28, 2022
    Abstract

    Internet of Things (IoT) is a technological innovation that defined interaction and computation of latest period. The objects of Internet of Things would empower by embedded gadgets whose limited sources has to be managed effectively. IoT usually means a network of devices connected through wireless network and interacts through internet. Resource management, particularly energy management, becomes a serious problem while devising IoT gadgets. Numerous researchers stated that routing and clustering were energy effectual solutions for optimum resource management in IoT setting. This study introduces a Modified Flower Pollination Algorithm based Resource Management (MFPA-RMM) model for Clustered IoT Environment. The presented MFPA-RMM model majorly focuses on the clustering the IoT devices in such a way that the resources are proficiently managed. The MFPA-RMM model is derived based on the fuzzy c-means (FCM) with FPA. The FPA approach is called heuristic algorithm has benefits of global optimization and faster convergence, therefore it was incorporated to FCM system for resolving the advantages and disadvantages of FCM method termed FCM-FPA mechanism. The result analysis of the MFPA-RMM model reported the enhanced performance of the MFPA-RMM model over other well-known techniques like LEACH and TEEN.

    Keywords :

    Clustering , Internet of Things , Heuristics , Flower pollination algorithm , Resource management

    References

    [1]          Abbas, F., Liu, G., Fan, P. and Khan, Z., 2020. An efficient cluster based resource management scheme and its performance analysis for V2X networks. IEEE Access, 8, pp.87071-87082.

    [2]          Munaye, Y.Y., Juang, R.T., Lin, H.P., Tarekegn, G.B. and Lin, D.B., 2021. Deep Reinforcement Learning Based Resource Management in UAV-Assisted IoT Networks. Applied Sciences, 11(5), p.2163.

    [3]          Sharma, M., Singla, M.K., Nijhawan, P. and Dhingra, A., 2021. Sensor-based optimization of energy efficiency in Internet of Things: A review. Sustainable Development Through Engineering Innovations, pp.153-161.

    [4]          Koo, S. and Lim, Y., 2021. A Cluster-Based Optimal Computation Offloading Decision Mechanism Using RL in the IIoT Field. Applied Sciences, 12(1), p.384.

    [5]          Geng, B., Li, Q. and Varshney, P.K., 2021. Utility-Theory-Based Optimal Resource Consumption for Inference in IoT Systems. IEEE Internet of Things Journal, 8(15), pp.12279-12288.

    [6]          Sharma, S. and Saini, H., 2020. Fog assisted task allocation and secure deduplication using 2FBO2 and MoWo in cluster-based industrial IoT (IIoT). Computer Communications, 152, pp.187-199.

    [7]          Salam, A., Javaid, Q. and Ahmad, M., 2021. Bio-inspired cluster–based optimal target identification using multiple unmanned aerial vehicles in smart precision agriculture. International Journal of Distributed Sensor Networks, 17(7), p.15501477211034071.

    [8]          Celik, E. and Dal, D., 2021. A novel simulated annealing-based optimization approach for clusterbased task scheduling. Cluster Computing, 24(4), pp.2927-2956.

    [9]          Apat, H.K., Bhaisare, K., Sahoo, B. and Maiti, P., 2020, March. Energy efficient resource management in fog computing supported medical cyber-physical system. In 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA) (pp. 1-6). IEEE.

    [10]       Zahoor, S. and Mir, R.N., 2021. Resource management in pervasive Internet of Things: A survey. Journal of King Saud University-Computer and Information Sciences, 33(8), pp.921-935.

    [11]       Desai, P.R., Mini, S. and Tosh, D.K., 2022. Edge-based Optimal Routing in SDN-enabled Industrial Internet of Things. IEEE Internet of Things Journal.

    [12]       Jaiswal, K. and Anand, V., 2021. A Grey-Wolf based Optimized Clustering approach to improve QoS in wireless sensor networks for IoT applications. Peer-to-Peer Networking and Applications, 14(4), pp.1943-1962

    [13]       Dogra, R., Rani, S., Verma, S., Garg, S. and Hassan, M.M., 2021. TORM: Tunicate Swarm Algorithmbased Optimized Routing Mechanism in IoT-based Framework. Mobile Networks and Applications, pp.1-9

    [14]       Khalid, A., ul Ain, Q., Qasim, A. and Aziz, Z., 2021. QoS based optimal resource allocation and workload balancing for fog enabled IoT. Open Computer Science, 11(1), pp.262-274

    [15]       Jumnal, A. and SM, D.K., 2020, January. Energy aware cluster based optimal virtual machine placement in cloud environment. In 2020 Fourth International Conference on Inventive Systems and Control (ICISC) (pp. 266-271). IEEE

    [16]       Liu, X., Jia, M. and Na, Z., 2019, January. Optimal Resource Optimization for Cluster-Based Energy- Efficient Cognitive IoT. In International Conference on Wireless and Satellite Systems (pp. 532-540). Springer, Cham

    [17]       Yang, X.S., 2012, September. Flower pollination algorithm for global optimization. In International conference on unconventional computing and natural computation (pp. 240-249). Springer, Berlin, Heidelberg.

     

    Cite This Article As :
    Gaber, Tarek. , Shieh, Chin-Shiuh. , Lin, Yuh-Chung. , Masmoudi, Fatma. Modified Flower Pollination Algorithm based Resource Management Model for Clustered IoT Network. International Journal of Wireless and Ad Hoc Communication, vol. , no. , 2022, pp. 97-106. DOI: https://doi.org/10.54216/IJWAC.040205
    Gaber, T. Shieh, C. Lin, Y. Masmoudi, F. (2022). Modified Flower Pollination Algorithm based Resource Management Model for Clustered IoT Network. International Journal of Wireless and Ad Hoc Communication, (), 97-106. DOI: https://doi.org/10.54216/IJWAC.040205
    Gaber, Tarek. Shieh, Chin-Shiuh. Lin, Yuh-Chung. Masmoudi, Fatma. Modified Flower Pollination Algorithm based Resource Management Model for Clustered IoT Network. International Journal of Wireless and Ad Hoc Communication , no. (2022): 97-106. DOI: https://doi.org/10.54216/IJWAC.040205
    Gaber, T. , Shieh, C. , Lin, Y. , Masmoudi, F. (2022) . Modified Flower Pollination Algorithm based Resource Management Model for Clustered IoT Network. International Journal of Wireless and Ad Hoc Communication , () , 97-106 . DOI: https://doi.org/10.54216/IJWAC.040205
    Gaber T. , Shieh C. , Lin Y. , Masmoudi F. [2022]. Modified Flower Pollination Algorithm based Resource Management Model for Clustered IoT Network. International Journal of Wireless and Ad Hoc Communication. (): 97-106. DOI: https://doi.org/10.54216/IJWAC.040205
    Gaber, T. Shieh, C. Lin, Y. Masmoudi, F. "Modified Flower Pollination Algorithm based Resource Management Model for Clustered IoT Network," International Journal of Wireless and Ad Hoc Communication, vol. , no. , pp. 97-106, 2022. DOI: https://doi.org/10.54216/IJWAC.040205