Title | ||
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Novel Hybrid-Cast Approach to Reduce Bandwidth and Latency for Cloud-Based Virtual Space. |
Abstract | ||
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In this article, we explore the possibility of enabling cloud-based virtual space applications for better computational scalability and easy access from any end device, including future lightweight wireless head-mounted displays. In particular, we investigate virtual space applications such as virtual classroom and virtual gallery, in which the scenes and activities are rendered in the cloud, with multiple views captured and streamed to each end device. A key challenge is the high bandwidth requirement to stream all the user views, leading to high operational cost and potential large delay in a bandwidth-restricted wireless network. We propose a novel hybrid-cast approach to save bandwidth in a multi-user streaming scenario. We identify and broadcast the common pixels shared by multiple users, while unicasting the residual pixels for each user. We formulate the problem of minimizing the total bitrate needed to transmit the user views using hybrid-casting and describe our approach. A common view extraction approach and a smart grouping algorithm are proposed and developed to achieve our hybrid-cast approach. Simulation results show that the hybrid-cast approach can significantly reduce total bitrate by up to 55% and avoid congestion-related latency, compared to traditional cloud-based approach of transmitting all the views as individual unicast streams, hence addressing the bandwidth challenges of the cloud, with additional benefits in cost and delay.
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Year | DOI | Venue |
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2018 | 10.1145/3205864 | TOMCCAP |
Keywords | Field | DocType |
Cloud-based mobile multimedia, hybrid-cast, virtual reality, virtual space | Wireless network,Broadcasting,Wireless,Virtual reality,Computer science,Computer network,Bandwidth (signal processing),Unicast,Cloud computing,Scalability | Journal |
Volume | Issue | ISSN |
14 | 3s | 1551-6857 |
Citations | PageRank | References |
1 | 0.35 | 9 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Xueshi Hou | 1 | 144 | 7.32 |
Yao Lu | 2 | 16 | 9.53 |
Sujit Dey | 3 | 3067 | 278.74 |