Proceedings Article10.1364/OFC.2020.W2A.29
Demonstration of AI-Assisted Energy-Efficient Traffic Aggregation in 5G Optical Access Network
Luyao Guan,Min Zhang,Danshi Wang +2 more
- 08 Mar 2020
- pp 1-3
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TL;DR: An AI-assisted energy-efficient traffic aggregation scheme, which is demonstrated in software-defined optical network testbed, can efficiently reduce energy consumption by traffic aggregation according to traffic prediction.
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Abstract: We propose an AI-assisted energy-efficient traffic aggregation scheme, which is demonstrated in software-defined optical network testbed. The experimental results show proposed scheme can efficiently reduce energy consumption by traffic aggregation according to traffic prediction.
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Static multi-sourced data retrieval in elastic optical networks
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Static multi-sourced data retrieval in elastic optical networks
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TL;DR: The erasure-coded multi-sourced data retrieval routing and scheduling problem is studied for static traffic in elastic optical networks, and the objective is to minimize the total transmission completion time of all the requests.
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- 01 Jan 2024
Reinforcement Learning Enabled Energy-Efficient Vbbu Pre-Migration in Cloud-Fog Based Elastic Optical Networks
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TL;DR: A reinforcement learning-based approach is proposed to optimize energy efficiency in cloud-fog elastic optical networks by pre-migrating vBBUs, achieving an 8.52% reduction in energy consumption while maintaining quality of service.
References
System-Level Modeling and Optimization of the Energy Efficiency in Cellular Networks—A Stochastic Geometry Framework
TL;DR: In this paper, a new closed-form analytical expression of the potential spectral efficiency (bit/sec/m2) was proposed for downlink cellular networks, which is obtained by generalizing the definition of coverage probability and by accounting for the sensitivity of the receiver not only during decoding of information data, but during the cell association phase as well.
Hierarchical edge cloud enabling network slicing for 5G optical fronthaul
TL;DR: Simulation results indicate that the proposed scheme is able to jointly allocate the bandwidth resources to network slices and realize cloud-computing offloading to meet various QoS requirements, and therefore reduce the fronthaul bandwidth burden.
93
Energy Efficient Optimization of Wireless-Powered 5G Full Duplex Cellular Networks: A Mean Field Game Approach
Xiaohu Ge,Haoming Jia,Yi Zhong,Yong Xiao,Yonghui Li,Branka Vucetic +5 more
- 11 Mar 2019
TL;DR: Simulation results indicate that the proposed strategy for the BSs to optimize the energy efficiency of 5G cellular networks with full duplex transmissions not only improves theEnergy efficiency but also ensures the average network coverage probability converges to a stable level.
27
Energy Optimization with Passive WDM Based Fronthaul in Heterogeneous Cellular Networking
Dexue Song,Jiawei Zhang,Yuming Xiao,Xin Wang,Yuefeng Ji +4 more
- 01 Oct 2018
TL;DR: A passive wavelength division multiplexing based fronthaul architecture for heterogeneous cellular networking, and a threshold based on/off algorithm for micro cells, and Simulation results show that the algorithm significantly saves energy than traditional solutions.
3
•Posted Content
System-Level Modeling and Optimization of the Energy Efficiency in Cellular Networks -- A Stochastic Geometry Framework
TL;DR: In this paper, a closed-form analytical expression of the potential spectral efficiency (bit/sec/m$^2$) was proposed for downlink cellular networks, which is obtained by generalizing the definition of coverage probability and by accounting for the sensitivity of the receiver not only during decoding of information data, but during the cell association phase as well.