可见光通信（VLC）与雾计算资源分配的节能联合优化
Energy-Efficient Joint Optimization of VLC and Fog Computing Resources Allocation
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中文总结 AI 辅助
本文针对室内VLC-PON回程网络架构，提出MILP模型联合优化VLC与雾计算资源分配，可降低平均总功耗，实现节能效果。
中文摘要 AI 辅助
本文研究一种室内网络架构，其中可见光通信（VLC）为用户与分布式雾计算资源提供无线连接，基于节能型无源光网络（PON）的回程网络将VLC接入点（AP）互连。我们研究VLC与雾计算资源分配的联合优化，目标是最小化处理与网络功耗。我们开发混合整数线性规划（MILP）模型，联合优化接入点（AP）选择、波长分配及雾计算资源分配，以响应用户请求。与基于最大化信干噪比（SINR）的静态预配置AP选择和波长分配（不考虑雾资源部署）相比，联合优化实现了更低的平均总功耗，这源于处理功耗的降低。这些节能效果归因于联合优化允许用户间共享AP，并选择仍满足服务质量（QoS）要求的更节能波长。
英文摘要
In this paper, we consider an indoor networking architecture in which visible light communication (VLC) provides wireless connectivity between users and distributed fog computing resources and an energy-efficient passive optical network (PON)- based backhaul interconnects the VLC access points (APs). We investigate the joint optimization of the allocation of VLC and fog computing resources aiming to minimize processing and networking power consumption. We develop a mixed-integer linear programming (MILP) model that jointly optimizes access points (APs) selection, wavelength assignment and fog computing resources allocation to serve the requests of users. Compared to a statically preconfigured AP selection and wavelength assignment based on maximizing signal-to-interference-plus-noise ratio (SINR) independently of fog resource placement, the joint optimization achieves lower average total power consumption, driven by a reduction in processing power. These savings are attributed to the ability of the joint optimization to allow AP sharing across users and selecting more energy-efficient wavelengths that still satisfy quality of service (QoS) requirements.
