FleXR: A System Enabling Flexibly Distributed Extended Reality

被引:0
作者
Heo, Jin [1 ]
Bhardwaj, Ketan [1 ]
Gavrilovska, Ada [1 ]
机构
[1] Georgia Inst Technol, Atlanta, GA 30332 USA
来源
PROCEEDINGS OF THE 2023 PROCEEDINGS OF THE 14TH ACM MULTIMEDIA SYSTEMS CONFERENCE, MMSYS 2023 | 2023年
关键词
distributed stream processing; extended reality; edge computing;
D O I
10.1145/3587819.3590966
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Extended reality (XR) applications require computationally demanding functionalities with low end-to-end latency and high throughput. To enable XR on commodity devices, a number of distributed systems solutions enable offloading of XR workloads on remote servers. However, they make a priori decisions regarding the offloaded functionalities based on assumptions about operating factors, and their benefits are restricted to specific deployment contexts. To realize the benefits of offloading in various distributed environments, we present a distributed stream processing system, FleXR, which is specialized for real-time and interactive workloads and enables flexible distributions of XR functionalities. In building FleXR, we identified and resolved several issues of presenting XR functionalities as distributed pipelines. FleXR provides a framework for flexible distribution of XR pipelines while streamlining development and deployment phases. We evaluate FleXR with three XR use cases in four different distribution scenarios. In the results, the best-case distribution scenario shows up to 50% less end-to-end latency and 3.9x pipeline throughput compared to alternatives.
引用
收藏
页码:1 / 13
页数:13
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