Paper Infomation
Research on Energy Consumption Optimization and Stability of IoT Devices in Complex Environments
Full Text(PDF, 64KB)
Author: Yinghao Tang
Abstract: The Internet of Things (IoT) has become an integral part of various industries, from smart cities to healthcare, driving the need for energy-efficient and stable devices, especially in complex and unpredictable environments. This research investigates the optimization of energy consumption and the enhancement of stability in IoT devices operating in such environments. The study addresses key challenges, including resource constraints, fluctuating environmental conditions, and the increasing complexity of IoT networks. It explores various energy optimization techniques, such as low-power communication protocols, edge and cloud computing, and machine learning models, that help reduce energy usage while maintaining performance. Furthermore, it examines stability enhancement strategies, including fault-tolerant mechanisms, resilient network architectures, and real-time monitoring and adaptive control, that ensure the continuous and reliable operation of IoT devices despite external disruptions. The findings of this research contribute to the development of next-generation IoT systems that are both energy-efficient and resilient, thereby promoting sustainable deployment in real-world applications.
Keywords: IoT Devices, Energy Consumption, Stability Enhancement, Complex Environments, Optimization Techniques, Machine Learning, Edge Computing
References:
[1] Yu S, Yanyi W, Gaoxiang J, et al. Deep learning-based power usage effectiveness optimization for IoT-enabled data center[J]. Peer-to-Peer Networking and Applications,2024,17(3):1702-1719.
[2] Yinghua T. Energy Consumption Optimization of an IoT Monitoring Center Based on a Max-Min Ant Colony Algorithm[J]. Wireless Communications and Mobile Computing,2023,2023
[3] Wang C W, Dwijendra A K N, Sayed T B, et al. Internet of Things Energy Consumption Optimization in Buildings: A Step toward Sustainability[J]. Sustainability,2023,15(8):
[4] Poh K L, Wei C C, Ling D T, et al. Optimizing Energy Consumption on Smart Home Task Scheduling using Particle Swarm Optimization[J]. Procedia Computer Science,2023,220195-201.
[5] Imran, Naeem I, Hyeun D K. IoT Task Management Mechanism Based on Predictive Optimization for Efficient Energy Consumption in Smart Residential Buildings[J]. Energy & Buildings,2022,257
[6] Ullah I, Fayaz M, Aman M, et al. An optimization scheme for IoT based smart greenhouse climate control with efficient energy consumption[J]. Computing,2021,104(2):1-25.
[7] Aladdin M, Muhannad A. Toward IoT fog computing-enabled system energy consumption modeling and optimization by adaptive TCP/IP protocol.[J]. Peer J. Computer science,2021,7e653-e653.
[8] Zhongyang W, Du X. Online optimization of intelligent reflecting surface-aided energy-efficient IoT-edge computing[J]. Future Generation Computer Systems,2023,141611-625.