Optimizing Route Scheduling Methods for Energy Efficiency in IoT-Enabled Green Computing Environments
- DOI
- 10.2991/978-94-6463-754-0_58How to use a DOI?
- Keywords
- Energy-Efficient Routing; IoT Networks; Green Computing; Reinforcement Learning; Dynamic Load Balancing
- Abstract
The proliferation of Internet of Things (IoT) devices has led to increased energy consumption in network infrastructures, necessitating the development of energy-efficient routing strategies. This paper proposes a novel route scheduling algorithm to minimize energy consumption while maintaining Quality of Service (QoS) in IoT-enabled green computing environments. Our approach optimizes data transmission paths based on real-time energy usage and network load by leveraging machine learning techniques and dynamic network reconfiguration. Experimental results demonstrate a 25% reduction in energy consumption compared to traditional routing methods, without compromising data delivery efficiency. This research contributes to the growing field of sustainable IoT systems and provides a framework for future advancements in energyaware network management.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - A. Hemantha Kumar AU - P. Vasuki PY - 2025 DA - 2025/06/30 TI - Optimizing Route Scheduling Methods for Energy Efficiency in IoT-Enabled Green Computing Environments BT - Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025) PB - Atlantis Press SP - 664 EP - 674 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-754-0_58 DO - 10.2991/978-94-6463-754-0_58 ID - Kumar2025 ER -