Efficient and Secure Data Aggregation for Resource-Constrained IoT Environments

The Internet of Things (IoT) has ushered in an era of interconnected devices and sensors that generate vast amounts of data.While the potential of IoT is vast, resource-constrained IoT environments present unique challenges, particularly in the context of data aggregation.This research focuses on developing secure data aggregation scheme tailored to resource-constrained IoT environments.In these settings, limitations on processing power, memory, and bandwidth necessitate innovative solutions to ensure both the efficiency and security of data collection and transmission.This research proposes a comprehensive framework that optimizes data aggregation algorithms.The key objectives of this research are to enhance data aggregation efficiency by minimizing redundant data transfer, optimizing data compression, and reducing the burden on constrained resources.The findings of this research provide valuable insights for IoT applications operating under resource limitations.By improving the efficiency and security of data aggregation in resource-constrained IoT environments, this research contributes to the realization of the full potential of IoT technologies in scenarios where resources are limited.