A View Synthesis-Based 360° VR Caching System Over MEC-Enabled C-RAN

Dai, Jianmei; Zhang, Zhilong; Mao, Shiwen; Liu, Danpu

doi:10.1109/tcsvt.2019.2946755

Cited by 66 publications

(41 citation statements)

References 36 publications

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“…Decoupling the problem into caching and routing optimizations, Lagrange partial relaxation method is applied to solve the problem. Dai et al [206] propose a synthesis-based VR caching scheme in C-RAN. Synthesis involves combining multiple views (e.g., texture and depth) to generate a multiview 360°video.…”

Section: B Collaborative Video Edge Deliverymentioning

confidence: 99%

Video Caching, Analytics, and Delivery at the Wireless Edge: A Survey and Future Directions

Jedari

Premsankar

Illahi

et al. 2021

IEEE Commun. Surv. Tutorials

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Section: B Collaborative Video Edge Deliverymentioning

confidence: 99%

Video Caching, Analytics, and Delivery at the Wireless Edge: A Survey and Future Directions

Jedari

Premsankar

Illahi

et al. 2021

IEEE Commun. Surv. Tutorials

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“…In [14], a Device-to-Device (D2D)assisted VR video distribution system and a pre-caching algorithm based on QoE gain were proposed. A view synthesisbased 360 • VR caching system was designed [15], where a hierarchical collaborative caching problem was formulated to minimize the transmission latency. To further improve the QoE of VR video services, [16]- [25] envisioned the joint computing-caching capabilities of edge network as the key enablers to obtain more potential gains.…”

Section: Related Workmentioning

confidence: 99%

“…Considering the randomness of user's head rotation, the probability that the VR device requests the viewpoint m ∈ P is denoted as q m , which characterizes how often the viewpoint m is tracked by the VR users as navigating the panoramic scene. According to [15], [28], we assume the viewpoint popularity as the uniform distribution, i.e., q m = 1 M . Besides, the sizes of 2D FOV and 3D FOV files of each viewpoint are denoted as S andS (bit), respectively.…”

Section: A User-centric Network Architecturementioning

confidence: 99%

A Cooperative Caching and Computing-Offloading Method for 3C Trade-Off in VR Video Services

Wang

Lü

2021

IEEE Access

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Virtual reality (VR) video services are becoming increasingly popular in Internet of Things (IoT) owing to its immersive experience. The realization of immersive experience relies on extremely large amount of data transmitted, restricting its application. To meet the transmission requirement of VR video services, this paper designs a user-centric network based on the mobile edge computing (MEC) framework, where the 2D/3D field of view (FOV) files can be cached and the projection process from 2D FOV to 3D FOV can be computed at the VR device or MEC servers collaboratively. Based on this, a cooperative caching and computing-offloading strategy is formulated as a decision matrix, and its optimal closed-form expression is obtained by minimizing the transmission requirement under the strict service time constraint to realize the trade-off between communication, caching and computing (3C trade-off). Besides, the effect of the transmission requirement on the network density is also analyzed to provide useful guidelines for network design. Simulation results demonstrate that the proposed method can achieve quasi-optimal performance compared with other contrasting schemes.

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“…However, these approaches are approaching their performance limit and sometimes they are too expensive to implement in practice. The rapid growth of video traffic and the emerging new video applications, such as Augmented reality (AR) and Virtual Reality (VR) [2], [3], bring about great challenges to the existing wireless networks.…”

Section: Introductionmentioning

confidence: 99%

“…This joint design approach is highly promising because caching alone may not be able to meet the fast growing demands of emerging video applications in 5G wireless and beyond. For example, in AR [2], [3], [15], video object classification and recognition task has to be performed first and then the videos are delivered to the user. In multi-viewpoint 360 degree interactive video transmission, the viewing-related features have to be analyzed at the edge first, then the video quality and other video transmission related parameters will be determined [16].…”

Section: Introductionmentioning

confidence: 99%

Joint Video Caching and Processing for Multi-Bitrate Videos in Ultra-Dense HetNets

Zhang

Mao

2020

IEEE Open J. Commun. Soc.

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Caching popular videos at the edge has been confirmed as a promising way to support low-latency video transmission and alleviate the backhaul traffic burden. Meanwhile, mobile edge computing (MEC) has also been regarded as an effective solution to meet the 5G low-latency service requirements. In this paper, we propose to fully utilize both the storage and computing resources at edge servers to support multiple bitrate video streaming. We design the video caching, processing, and user association models that aim to minimize the average retrieval latency of all users. This problem is modeled as a mixed-integer bilinear problem, which is NP-hard. We show that under practical constraints on storage, bandwidth, and processing capacity, the problem does not exhibit sub-modular property and the performance of a greedy algorithm may not be strictly guaranteed. To deal with this challenging problem, we decompose the original problem into a cache placement problem and a user-BS association problem, while still preserving the interplay between the two sub-problems. A linearization and rounding algorithm, including: (i) a greedy rounding proactively caching scheme and (ii) a random-rounding user-BS association scheme, is then proposed, with performance bounds derived. Extensive simulation results show that the proposed scheme can achieve a near-optimal performance under various storage, computing capacity, and downlink bandwidth settings.Index Terms-Video caching, video transcoding, multiple bitrate video, mobile edge computing (MEC), submodularity.

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A View Synthesis-Based 360° VR Caching System Over MEC-Enabled C-RAN

Cited by 66 publications

References 36 publications

Video Caching, Analytics, and Delivery at the Wireless Edge: A Survey and Future Directions

Video Caching, Analytics, and Delivery at the Wireless Edge: A Survey and Future Directions

A Cooperative Caching and Computing-Offloading Method for 3C Trade-Off in VR Video Services

Joint Video Caching and Processing for Multi-Bitrate Videos in Ultra-Dense HetNets

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