## 2 Related Work  
Many works have been completed, ranging from those focusing on the underlying FiWi infrastructures to the top-level, time-sensitive services in the tactile internet.  
[PERSON] et al. held that different applications demand different levels of intelligence and efficiency in data-processing [11]. Multi-tier computing for real-time, data-streaming processing, which integrates cloud-, fog-, and edge-computing, associated with offloading, was required for intelligent, tactile internet applications. [PERSON] et al. derived the exact expressions of a typical Voronoi area of a multi-tier Poisson network with a generalized association rule [12].  
[PERSON] et al. surveyed the future 6G vision of IoT and its convergence with the radio-over-fiber (RoF) system. They deemed that the RoF-based FiWi network was one of the most promising enablers of 6G IoT [13]. To achieve 6G, highly efficient data training or computing was absolutely necessary.  
[PERSON] et al. pointed out that the internet of everything in 5G would transform into the internet of no-things and provided an experiment looking at how the internet of no-things served as a useful stepping stone toward the far-reaching vision of future 6G networks [14]. The internet of no-things that they mentioned referred to the internet's unnoticed and silent integration into people's lives. From the perspective of network evolution, low latency is significant.  
To cope with the problem that IoT devices do not have enough available capacity to collaboratively co-host newly emerged tasks, [PERSON] et al. proposed a novel resource allocation and service co-placement (RaSP) algorithm [15]. These tasks were latency-aware, online, and re-configurable. [PERSON] et al. proved that the latency was a stubborn bottleneck for tactile internet applications. They thought that the edge-based AI forecasting algorithm could alleviate this dilemma [16].  
[PERSON] et al. concentrated on minimizing the overall latency under the quality of service (QoS) in the indoor, multimode, radio-frequency-optical, heterogeneous network, without considering the outdoor environment [17]. [PERSON] et al. conducted a software-defined, time-sensitive networking experiment [18]. They demonstrated that the time synchronization of cross-domain interconnection was helpful to reduce latency. However, the underlying network infrastructure was neglected.  
[PERSON] et al. studied the different delay requirements in a FiWi-enhanced, heterogeneous, cloud radio-access network (H-CRAN) with MEC and offloading. A decentralized algorithm that maximized the utility of all users while meeting the delay requirement of different services was proposed [19]. Only wireless mobile communication was taken into consideration in their work.  
[PERSON] et al. investigated the delay minimization problem for task offloading in a hierarchical, fog-computing C-RAN network [20]. In the formulated MINLP, they minimized the total delay in the computing tasks by optimizing the receive beamforming vectors, task allocation, each server's computing speed for offloading tasks, and the bandwidth of fronthaul links. Note that the wireless communication in the C-RAN network was realized via the single-hop link. Their work is most relevant to ours. In our work, the wireless part was the multi-hop link. The wire part was a fiber network, while their work had no specifications for the wire part. They also did not consider the application of tactile internet services.