Energy-Aware Network Management for IoT Devices in Smart Cities

Abstract

In the modern era of rapid urbanization, smart cities are emerging as data-driven ecosystems where Internet of Things (IoT) devices play a crucial role in enhancing efficiency across urban services. However, the proliferation of these devices has resulted in significant energy consumption, posing challenges for sustainable city development. Effective energy management in IoT networks is thus essential to achieve long-term sustainability goals. This paper addresses the issue of energy inefficiency within IoT networks in smart cities by proposing an Energy-Aware Network Management (EANM) framework. Our methodology integrates an adaptive clustering algorithm and a predictive analytics model, forecasting network load and energy demands based on historical data patterns. By leveraging machine learning, the framework enables the real-time adaptation of network protocols, including sleep scheduling and data transmission frequency adjustments, to reduce unnecessary power consumption. We conducted simulations to evaluate the framework's effectiveness using various IoT devices under diverse environmental conditions. Results demonstrate a substantial reduction in energy consumption, with up to 30% savings in high-density IoT environments, without compromising network performance or data accuracy. This research highlights the potential of intelligent EANM in ensuring sustainable energy usage within IoT-driven smart cities. By reducing the energy footprint of IoT devices, this framework extends the operational life of devices and contributes to reducing the overall carbon emissions associated with large-scale IoT deployments. The findings underscore the necessity of adopting adaptive energy management strategies to address the escalating demands of urban services, supporting smart city sustainability initiatives. This approach has significant implications for advancing IoT network efficiency, promoting eco-friendly urban development, and paving the way for more resilient smart city infrastructures.