Optimum resource allocation in optical wireless systems with energy-efficient fog and cloud architectures
Optimum resource allocation in optical wireless systems with energy-efficient fog and cloud architectures
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DOI：
10.1098/rsta.2019.0188
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发表时间：
2020-04-17
期刊：
影响因子：
5
通讯作者：
Elmirghani, Jaafar M. H.
中科院分区：
文献类型：
--
作者：
Alsulami, Osama Zwaid;Alahmadi, Amal A.;Elmirghani, Jaafar M. H.
光无线通信（OWC）是一种很有前途的技术，可以提供高数据速率，同时支持多个用户。光无线（OW）物理层已经得到了广泛的研究，但很少有工作致力于多址接入和OW前端如何连接到网络。在本文中，OWC系统采用波分多址（WDMA）方案进行了研究，以支持多个用户的目的。此外，首次提出了云/雾架构，为OWC提供处理能力。云/雾集成架构使用可见室内光来创建与潜在移动的节点的高数据速率连接。这些OW节点被进一步集群化，并用作雾迷你服务器，通过OW通道为其他用户提供处理服务。额外的雾处理单元位于房间，建筑物，校园和地铁层。进一步的处理能力由远程云站点提供。提出了两种混合整数线性规划（MILP）模型，用于数值研究OW系统的组网和处理。第一个MILP模型被开发并用于优化室内OWC系统中的资源分配，特别是向用户分配接入点（AP）和波长，而第二个MILP模型被开发用于优化不同雾和云节点中的处理任务的放置。利用MILP模型分析了云/雾一体化体系结构中的任务布局优化问题。考虑了多个场景，其中移动的节点位置在房间中变化，并且每个OW节点所请求的处理量和数据速率变化。结果有助于确定最佳的颜色和AP用于通信的一个给定的移动的节点位置和OWC系统配置，最佳位置放置处理和网络架构的影响。这篇文章是主题问题的一部分“光无线通信”。
Optical wireless communication (OWC) is a promising technology that can provide high data rates while supporting multiple users. The optical wireless (OW) physical layer has been researched extensively, however, less work was devoted to multiple access and how the OW front end is connected to the network. In this paper, an OWC system which employs a wavelength division multiple access (WDMA) scheme is studied, for the purpose of supporting multiple users. In addition, a cloud/fog architecture is proposed for the first time for OWC to provide processing capabilities. The cloud/fog-integrated architecture uses visible indoor light to create high data rate connections with potential mobile nodes. These OW nodes are further clustered and used as fog mini servers to provide processing services through the OW channel for other users. Additional fog-processing units are located in the room, the building, the campus and at the metro level. Further processing capabilities are provided by remote cloud sites. Two mixed-integer linear programming (MILP) models were proposed to numerically study networking and processing in OW systems. The first MILP model was developed and used to optimize resource allocation in the indoor OWC systems, in particular, the allocation of access points (APs) and wavelengths to users, while the second MILP model was developed to optimize the placement of processing tasks in the different fog and cloud nodes available. The optimization of tasks placement in the cloud/fog-integrated architecture was analysed using the MILP models. Multiple scenarios were considered where the mobile node locations were varied in the room and the amount of processing and data rate requested by each OW node was varied. The results help to identify the optimum colour and AP to use for communication for a given mobile node location and OWC system configuration, the optimum location to place processing and the impact of the network architecture.This article is part of the theme issue 'Optical wireless communication'.