EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 15(5): e1

Research Article

Energy Harvesting Aware Clustering and Opportunistic Transmission with Fuzzy Petri Net Reasoning

  • @ARTICLE{10.4108/eai.17-9-2015.150283,
        author={Aya  Mostafa and Khaled  Hassan},
        title={Energy Harvesting Aware Clustering and Opportunistic Transmission with Fuzzy Petri Net Reasoning},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={2},
        number={5},
        publisher={EAI},
        journal_a={INIS},
        year={2015},
        month={9},
        keywords={energy harvesting, fuzzy petri nets reasoning, wireless sensor networks, clustering algorithms},
        doi={10.4108/eai.17-9-2015.150283}
    }
    
  • Aya Mostafa
    Khaled Hassan
    Year: 2015
    Energy Harvesting Aware Clustering and Opportunistic Transmission with Fuzzy Petri Net Reasoning
    INIS
    EAI
    DOI: 10.4108/eai.17-9-2015.150283
Aya Mostafa1, Khaled Hassan1,*
  • 1: Faculty of Information Engineering and Technology (IET) German University in Cairo, New Cairo, Egypt
*Contact email: khaled.shawky@guc.edu.eg

Abstract

As a solution to the environmental and natural disaster monitoring and detection, we propose an energy efficient large-scale autonomous Wireless Sensor Networks (WSNs) that can withstand the limited battery lifetime problem. Hereto, an energy-harvesting (EH) aware clustering technique is introduced using a knowledge-based inference approach for selecting cluster heads using fuzzy petri nets with three level hierarchy. Our EH mechanism endorses the sensor nodes with hybrid sources EH giving a potential boost for the network life. The robustness of our WSN is addressed by introducing a primary and a secondary backups for each level to reduce the frequency of reclustering. Finally, an opportunistic energy harvesting aware transmission technique is presented to enhance the network life-time. The performance of this scheme is evaluated against the famous clustering techniques, where the proposed algorithms extend the WSN field life-time significantly.