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Smart city article details
| Title | A Novel Load-Driven Location-And Power-Aware Eo-Based Iot-Wsn Clustering And Routing Protocol For Sustainable Smart Cities |
|---|---|
| ID_Doc | 3423 |
| Authors | Darabkh K.A.; Al-Akhras M. |
| Year | 2025 |
| Published | IEEE Internet of Things Journal |
| DOI | http://dx.doi.org/10.1109/JIOT.2025.3574636 |
| Abstract | The Internet of Things (IoT) has impacted sectors like smart cities and healthcare by enabling real-time data collection through Wireless Sensor Networks (WSNs). However, challenges such as limited battery life, connectivity disruptions, and the separate management of clustering and routing hinder performance and energy efficiency. Existing cluster-based IoT-WSN routing protocols often suffer from issues such as random or non-energy-aware Cluster Head (CH) selection, imbalanced energy consumption, imperfect load balancing, and a lack of integration between clustering and routing. These shortcomings reduce overall network efficiency. To address these challenges, we propose the Load-Driven, Location-and Power-aware Equilibrium Optimizer-Based Clustering and Routing Protocol (LDLP-EO-CRP), which integrates clustering and routing to optimize CH selection and balance energy consumption. LDLP-EO-CRP is designed for sustainable smart city applications, including smart waste management, energy-efficient street lighting, air quality monitoring, and intelligent traffic management. By enabling IoT systems to operate reliably over extended periods, LDLP-EO-CRP supports continuous, real-time data collection and monitoring, contributing to citywide sustainability goals and enhancing urban resilience. The proposed protocol divides the sensing area into hexagonal clusters, adapting to changes in network size, node distribution, and density. Each cluster is managed by a CH selected using the EO algorithm, which considers key factors through its fitness function, namely, the remaining energy of sensor nodes, their distances from the sink, loads, and proximities to neighboring nodes. LDLP-EO-CRP incorporates a novel relay-based data forwarding technique, where each CH transfers data hop-by-hop to the sink, based on the loads and proximities of candidate relay nodes. Simulation results demonstrate that LDLP-EO-CRP outperforms existing protocols, extending network lifespan, increasing throughput, reducing delay, and optimizing energy usage. © 2014 IEEE. |
| Author Keywords | Average Delay; Dynamic Clustering; Energy Efficiency; Equilibrium Optimizer; Internet of Things; Network Lifespan; Routing; Throughput |
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