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IDCT: Intelligent Data Collection Technique for IoT-Enabled Heterogeneous Wireless Sensor Networks in Smart Environments

Walid OsamyComputer Science Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha, EgyptAhmed SalimDepartment of Computer Science, College of Sciences and Arts, Qassim University, Buraidah, Al-Mithnab, Saudi ArabiaAhmed M. KhedrComputer Science Department, University of Sharjah, Sharjah, United Arab EmiratesAhmed El-SawyComputer Science Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt
2021en
ABI

Annotatsiya

Wireless Sensor Networks (WSNs) lend themselves to a wide variety of applications in our daily lives, such as environmental monitoring, safety, health-care, animal monitoring, etc. However, one of the key issues in WSN is energy constraints. This makes energy-conservation one of the major keys to the efficient functioning and lifetime of WSN. In this paper, given a network of nodes with heterogeneous energy, our goal is to determine energy-aware disjoint dominating sets (DSs) that work as data collection nodes in each round, to improve overall WSN lifetime. In order to accomplish this goal, we propose an intelligent data collection technique with two phases, the collector nodes selection, and the data gathering path formation and collection phases. In the collector nodes selection phase, an energy-aware algorithm based on swarm intelligence is proposed to construct disjoint dominating sets that work as collector nodes in each round. In the data gathering path formation and collection phase, data gathering path is determined for achieving maximal data collection efficiency and reduced energy consumption. The efficiency of our proposed technique is proved mathematically and through simulations.

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