STRATEGIES TO INCREASE NETWORK ENERGY EFFICIENCY
DOI:
https://doi.org/10.56292/SJFSU/vol31_iss6/a203Keywords:
Network energy, energy efficiency, adaptive link rate, sleep mode, load balancing, artificial intelligence, energy/bit metric.Abstract
Abstract
This article provides an in-depth analysis of the issue of improving energy efficiency in modern computer networks. The study examines three main approaches: Adaptive Link Rate (ALR), Traffic-aware Sleep Modes (TSM), and AI-driven Load Consolidation (AILC). Simulation results demonstrate that individual strategies can achieve energy savings of 18–35%, while their combined application can increase energy efficiency by up to 48.7%. Furthermore, the observed changes in quality of service indicators remain within acceptable limits, making these strategies highly promising for practical implementation.
References
1. Tanenbaum A. S. Computer Networks. — Pearson Education, 2019.
2. IEEE 802.3az Energy Efficient Ethernet Standard.
3. Baliga J., Ayre R. W., Tucker R. S. Energy consumption in IP networks. Optical Communications and Networking, 2010.
4. Gupta M., Singh S. Greening of the Internet. Proceedings of ACM SIGCOMM, 2003.
5. Muallif tomonidan ishlab chiqilgan model va simulyatsiya natijalari
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Scientific journal of the Fergana State University
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
How to Cite
Most read articles by the same author(s)
- Umarov Bekzod Azizovich, ANALYSIS OF PROTOCOLS IN CONNECTING IOT DEVICES TO THE NETWORK , Scientific journal of the Fergana State University: No. 6 (2025): FarDU. Ilmiy xabarlar jurnali (Aniq fanlar)