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SIoT: A New Strategy to Improve the Network Lifetime with an Efficient Search Process

Author

Listed:
  • Abderrahim Zannou

    (LISAC Laboratory, Sidi Mohamed Ben Abdellah University, Fes 30050, Morocco)

  • Abdelhak Boulaalam

    (LISA Laboratory, Sidi Mohamed Ben Abdellah University, Fes 30050, Morocco)

  • El Habib Nfaoui

    (LISAC Laboratory, Sidi Mohamed Ben Abdellah University, Fes 30050, Morocco)

Abstract

The Social Internet of Things (SIoT) means that every node can use a set of nodes that are considered as friends to search for a specific service. However, this is a slow process because each node is required to manage a high number of friends. Thus, the SIoT issue consists of how to select the right friends that improve the network navigability. The enhancement of the network navigability boosts the search for a service to be rapid but not guaranteed. Furthermore, sending requests from the shortest paths involves the rapid search, but the network lifetime can be reduced due to the number of requests that can be transmitted and processed by the nodes that have low power energy. This paper proposes a new approach that improves the network navigability, speeds up the search process, and increases the network lifetime. This approach aims at creating groups dynamically by nodes where each group has a master node, second, using a consensus algorithm between master nodes to agree with a specific capability, finally adopting a friendship selection method to create a social network. Thus, the friends will be sorted periodically for the objective of creating simultaneously a balance between the energy consumption and the rapid search process. Simulation results on the Brightkite location-based online social network dataset demonstrate that our proposal outperforms baseline methods in terms of some parameters of network navigability, path length to reach the providers, and network lifetime.

Suggested Citation

  • Abderrahim Zannou & Abdelhak Boulaalam & El Habib Nfaoui, 2020. "SIoT: A New Strategy to Improve the Network Lifetime with an Efficient Search Process," Future Internet, MDPI, vol. 13(1), pages 1-23, December.
  • Handle: RePEc:gam:jftint:v:13:y:2020:i:1:p:4-:d:469800
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    References listed on IDEAS

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    Cited by:

    1. Soukaina Bouarourou & Abderrahim Zannou & El Habib Nfaoui & Abdelhak Boulaalam, 2023. "An Efficient Model-Based Clustering via Joint Multiple Sink Placement for WSNs," Future Internet, MDPI, vol. 15(2), pages 1-27, February.
    2. Abdelghani Dahou & Samia Allaoua Chelloug & Mai Alduailij & Mohamed Abd Elaziz, 2023. "Improved Feature Selection Based on Chaos Game Optimization for Social Internet of Things with a Novel Deep Learning Model," Mathematics, MDPI, vol. 11(4), pages 1-17, February.
    3. Antonios Pliatsios & Dimitrios Lymperis & Christos Goumopoulos, 2023. "S2NetM: A Semantic Social Network of Things Middleware for Developing Smart and Collaborative IoT-Based Solutions," Future Internet, MDPI, vol. 15(6), pages 1-27, June.

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