Virtual Reality (VR), together with the network infrastructure, can provide an interactive and immersive experience for multiple users simultaneously and thus enables collaborative VR applications (e.g., VR-based classroom). However, the satisfactory user experience requires not only high-resolution panoramic image rendering but also extremely low latency and seamless user experience. Besides, the competition for limited network resources (e.g., multiple users share the total limited bandwidth) poses a significant challenge to collaborative user experience, in particular under the wireless network with time-varying capacities. While existing works have tackled some of these challenges, a principled design considering all those factors is still missing. In this paper, we formulate a combinatorial optimization problem to maximize the Quality of Experience (QoE), defined as the linear combination of the quality, the average VR content delivery delay, and variance of the quality over a finite time horizon. In particular, we incorporate the influence of imperfect motion prediction when considering the quality of the perceived contents. However, the optimal solution to this problem can not be implemented in real-time since it relies on future decisions. Then, we decompose the optimization problem into a series of combinatorial optimization in each time slot and develop a low-complexity algorithm that can achieve at least 1/2 of the optimal value. Despite this, the trace-based simulation results reveal that our algorithm performs very close to the optimal offline solution. Furthermore, we implement our proposed algorithm in a practical system with commercial mobile devices and demonstrate its superior performance over state-of-the-art algorithms. We open-source our implementations on https://github.com/SNeC-Lab-PSU/ICDCS-CollaborativeVR.
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A Reality-Conforming Approach for QoS Performance Analysis of AFDX in Cyber-Physical Avionics Systems
AFDX (Avionics Full Duplex Switched Ethernet) is developed to support mission-critical communications while providing deterministic Quality of Service (QoS) across cyber-physical avionics systems. Currently, AFDX utilizes FP/FIFO QoS mechanisms to guarantee its real-time performance. To analyze the real-time performance of avionic systems in their design processes, existing work analyzes the deterministic delay bound of AFDX using NC (Network Calculus). However, existing analytical work is based on an unrealistic assumption leading to assumed worst cases that may not be achievable in reality. In this paper, we present a family of algorithms that can search for realistic worst-case delay scenarios in both preemptive and non-preemptive situations. Then we integrate the proposed algorithms with NC and apply our approach to analyzing tandem AFDX networks. Our reality-conforming approach yields tighter delay bound estimations than the state of the art. When there are 100 virtual links in AFDX networks, our method can provide delay bounds more than 25% tighter than those calculated by the state of the art in our evaluation. Moreover, when using our reality-conforming method in the design process, it leads to 27.2% increase in the number of virtual links accommodated by the network in the tandem scenario.
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- NSF-PAR ID:
- 10297125
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- 2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS)
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IWQOS52092.2021.9521335
