Virtual Reality, Augmented Reality, and Edge Computing

Virtual Reality (VR) enhances our physical environment by artificially rendering a real environment using audio and visual
features. VR systems are expected to completely change how we interact with the world through a new virtualized
immersive environment with unprecedented experiences where users will feel part of it.

Although VR systems have attracted considerable attention in recent years, it has been considered a “killer” use case of the
5G networks due to stringent VR application requirements. As a result, the adoption of VR technology remains hampered for a variety of reasons: (i) Head-Mounted Displays (HMDs) hardware limitation and costs; (ii) HMDs’ resolution and visual quality remain low; and (iii) mobility remains an issue and impacts usability. The reasons given may lead to an unsatisfactory VR user experience.

A primary latency bottleneck lies in the fact that VR systems are composed of multiple compute-intensive components, e.g.,
motion prediction, Field of View (FoV) prediction, hands tracking, encoding, decoding, etc. On the one hand, tethered VR HMDs might acquire specialized hardware platforms, e.g., PCs or consoles. On the other hand, standalone VR HMDs, i.e., physical freedom by removing the cables from PCs or consoles, may not support specialized hardware platforms due to the requirements of Mobile Virtual Reality (MVR) applications, .e.g, user freedom.

One promising way to address the VR technical limitations is Multi-access Edge Computing (MEC), especially the network
latency, which implements computing and service delivery at the edge networks. MEC also supports the compute-intensive task deployment of VR applications to mitigate the high computing latency.

VR has posed several challenges to the current VR HMDs technology domain and the network infrastructure in supporting ultra-high throughput and ultra-low latency due to: (i) The current VR HMDs fail to satisfy the computing latency requirements for MVR applications; (ii) Today’s VR HMDs do not support the necessary energy demands; and (iii) The cloud computing architecture does not support the network latency requirements for ultimate VR applications.

The goal of this thesis is to investigate how the MEC infrastructure supports the deployment of compute-intensive tasks of VR applications during user mobility, considering the stringent computing and networking latency requirements for such applications as well as the MEC infrastructure limitations. As a result, this thesis aims to answer the following questions:

1.  How would VR refactoring overcome the computational power required by VR HMDs?

2. What are the benefits of MEC to support VR-intensive computing tasks?

3. How to manage several VR service functions, each featuring distinct policies and requirements?

Related Literature:

1. Mangiante, Simone, et al. "Vr is on the edge: How to deliver 360 videos in mobile networks." Proceedings of the Workshop on Virtual Reality and Augmented Reality Network. 2017.
2. Bastug, Ejder, et al. "Toward interconnected virtual reality: Opportunities, challenges, and enablers." IEEE Communications Magazine 55.6 (2017): 110-117.
3. Lai, Zeqi, et al. "Furion: Engineering high-quality immersive virtual reality on today's mobile devices." IEEE Transactions on Mobile Computing 19.7 (2019): 1586-1602.
4. You, Dongho, et al. "Fog computing as an enabler for immersive media: Service scenarios and research opportunities." IEEE Access 7 (2019): 65797-65810.
5. Siriwardhana, Yushan, et al. "A Survey on Mobile Augmented Reality With 5G Mobile Edge Computing: Architectures, Applications, and Technical Aspects." IEEE Communications Surveys & Tutorials 23.2 (2021): 1160-1192.

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