Flower Pollination Algorithm–Based Cluster Head Optimization And Compression-Aware Data Transmission For Iot-Driven Wireless Sensor Networks
DOI:
https://doi.org/10.29284/adysgy39Keywords:
Wireless sensor network, IoT, Data compression, Optimization, ClusteringAbstract
Wireless Sensor Networks (WSNs) form a fundamental component of Internet of Things (IoT)–based environmental monitoring systems; however, their practical deployment is severely constrained by limited energy resources and excessive communication overhead. Although clustering-based protocols are widely used to enhance network lifetime, most existing solutions emphasize only optimal cluster head (CH) selection and rely on direct or inefficient data transmission strategies, leading to rapid energy depletion. Moreover, the large volume of time-series weather data generated by sensor nodes further intensifies energy consumption during transmission. To address these challenges, this paper proposes an integrated optimization framework that jointly considers energy-aware CH selection and compression-based data transmission. The Flower Pollination Algorithm (FPA), inspired by natural pollination behavior, is employed to select an optimal set of CHs based on multiple network parameters, including residual energy, node distribution, convergence, divergence, centrality, and distance to the Base Station (BS). Under the stage of data aggregation at the CHs, simple, fast but efficient compression methods—known as ASWDR and Zstandard (ZSTD)—are applied. This data compression stage is used for reducing the size of data before the transmission from CHs to the BS. The results generated under simulation model are used to demonstrate the proposed FPA-based CHs selection associated with data compression reduce energy consumption significantly. Hence it introduces the performance improvement in terms of load balancing, network stability, and prolonging the lifetime of network compared to conventional and other optimization-based protocols for sustainable and energy-efficient WSN-based IoT applications.
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