ELBPFO: Energy-Aware Load Balanced Packet Failure Optimization for Provisioning Time-Driven IoT Application using Wireless Sensor Networks

Abstract

Ensuring efficient and reliable data transmission is crucial for time-driven Internet of Things (IoT) applications using Wireless Sensor Networks (WSNs). These applications require optimized communication strategies that minimize latency and energy consumption while maintaining network stability in heterogeneous environments. However, achieving real-time data delivery often leads to excessive energy depletion and increased packet failures, particularly in sensor nodes near the sink. Traditional clustering approaches help manage energy consumption but introduce additional load imbalances and energy burdens on cluster heads, impacting overall network efficiency. To address these challenges, this study proposes Energy-Aware Load Balanced Packet Failure Optimization (ELBPFO), a strategy designed to enhance network lifetime and reduce packet loss while ensuring energy-efficient data transmission. ELBPFO optimizes clustering and routing mechanisms to balance network load, minimize hop count, and lower communication delay, thereby improving the performance of time-sensitive IoT applications. Comparative analysis demonstrates that ELBPFO outperforms conventional models in reducing latency and energy consumption, making it a robust solution for real-time IoT-WSN deployments.