## 3 Related Works  
In recent years, numerous approaches and optimization models have been proposed for addressing the challenges of mobile devices using MEC by applying the computation offloading concept. Most of these studies handle only two levels of computation offloading in MEC systems [20; 21], while few studies address the multi-level computation offloading [22]. In this section, a brief overview of the common approaches will be introduced. [PERSON] et al. [30] introduced a 5G City and discussed how the advanced media services will be facilitated using 5G technology such as ultra-high-definition video, augmented and virtual reality. In addition, the opportunities provided by 5G technology and changes in the work of the telecommunications service provider are being studied. Furthermore, three different use cases are presented and their use in public networks, as well as the advantages of using this model for infrastructure owners and media service providers, is described. While in [31], [PERSON] et al. studied the problem of low-latency wireless networks of virtual reality. Then, to solve this problem, the authors proposed to use information about user positions, proactive computing and caching to minimize computation latency. Real prototypes for VR applications were implemented in which some of them used edge computing [32; 33], while other prototypes did not use edge computing [34; 35]. For the prototypes which used edge computing, [PERSON] et al. discussed how to enable a portable and mobile VR device with VR glasses for wireless connecting to edge computing devices in [32]. In addition, the authors explored the main issues which are associated with the inclusion of a new approach to wireless VR with edge computing and various application scenarios. Furthermore, they provided an analysis of the delay requirements to enable wireless VR, and to study several possible solutions. Whereas, the computation offloading for VR gaming applications has been considered in [33] in which minimizing the network latency is the main goal. Meanwhile, in [34], [PERSON] et al. dealt with issues related to information security and addressed the existing security system shortcomings in augmented reality (AR) technologies, artificial intelligence, wireless, 5G, big data, massive computing and virtual stores. While in [35], [PERSON] et al. addressed the computation offloading over mmWave for mobile VR in which 360 video streaming is used as a case study. First, the authors mentioned that using 360 video streaming requires more bandwidth and faster user response. In addition, mobile virtual reality (VR) devices locally process video decoding, post-processing and rendering. However, its performance is not enough for streaming high-resolution video, such as 4 K-8 K. Therefore, the authors propose adaptive computations of a discharge scheme using a millimeter-wave (mm-wave) communication. This offloading scheme helps the mobile device to share video decoding tasks on a powerful PC. This improves the mobile device VR ability to play high-definition video. mmWave 802.11 ad wireless technology promises the use of broadband wireless to improve the throughput of multimedia systems. In 5G, network AR/VR applications will be one of the leading applications in the category of Ultra-Reliable and Low-Latency Communication [20; 36]. More specifically, in [20], [PERSON] et al. proposed a computation offloading framework for Ultra-Reliable Low Latency communications in which the computation tasks are divided into sub-tasks that will be offloaded and executed at nearby edge server nodes. In addition, the authors formulated optimization problems which jointly minimize the latency and offloading failure probability. Furthermore, three heuristic search-based algorithms are designed to solve this problem and derive the computation offloading decision. However, cloud computing does not consider environment in this work, which can leverage when the edge server resources are not enough. Similarly, in [36] [PERSON] et al.