Research Area: Wireless Sensor Networks
Energy-efficient and reliable data gathering using highly stable links in underwater wireless sensor networks (UWSNs) is challenging because of time and location-dependent communication characteristics of the acoustic channel. In this paper, we propose a novel dynamic firefly mating optimization inspired routing scheme called FFRP for the internet of UWSNs-based events monitoring applications. The proposed FFRP scheme during the events data gathering employs a self-learning based dynamic firefly mating optimization intelligence to find the highly stable and reliable routing paths to route packets around connectivity voids and shadow zones in UWSNs. The proposed scheme during conveying information minimizes the high energy consumption and latency issues by balancing the data traffic load evenly in a large-scale network. In additions, the data transmission over highly stable links between acoustic nodes increases the overall packets delivery ratio and network throughput in UWSNs. Several simulation experiments are carried out to verify the effectiveness of the proposed scheme against the existing schemes through NS2 and AquaSim 2.0 in UWSNs. The experimental outcomes show the better performance of the developed protocol in terms of high packets delivery ratio (PDR) and network throughput (NT) with low latency and energy consumption (EC) compared to existing routing protocols in UWSNs.
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Author(s) Name: Muhammad Faheem; Rizwan Aslam Butt; Basit Raza; Hani Alquhayz; Muhammad Waqar Ashraf; Saleem Raza; MD. Asri Bin Ngadi
Journal name: IEEE Access
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Publisher name: IEEE
DOI: 10.1109/ACCESS.2020.2976105
Volume Information: Volume 9,Page(s): 39587 - 39604
