Award Abstract # 1750890
CAREER: Improving Mobile Video Delivery for Emerging Contents and Networks

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: TRUSTEES OF INDIANA UNIVERSITY
Initial Amendment Date: March 19, 2018
Latest Amendment Date: March 19, 2018
Award Number: 1750890
Award Instrument: Continuing Grant
Program Manager: Alexander Sprintson
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: May 1, 2018
End Date: April 30, 2019 (Estimated)
Total Intended Award Amount: $556,633.00
Total Awarded Amount to Date: $107,530.00
Funds Obligated to Date: FY 2018 = $0.00
History of Investigator:
  • Feng Qian (Principal Investigator)
    fqian7@gmail.com
Recipient Sponsored Research Office: Indiana University
107 S INDIANA AVE
BLOOMINGTON
IN  US  47405-7000
(317)278-3473
Sponsor Congressional District: 09
Primary Place of Performance: School of Informatics and Computing, Indiana University
150 S. Woodlawn Ave
Bloomington
IN  US  47405-7104
Primary Place of Performance
Congressional District:
09
Unique Entity Identifier (UEI): YH86RTW2YVJ4
Parent UEI:
NSF Program(s): Networking Technology and Syst
Primary Program Source: 01001819DB NSF RESEARCH & RELATED ACTIVIT
01001920DB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT

01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 1045
Program Element Code(s): 736300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Streaming videos wirelessly on mobile devices is an increasingly important application. The objective of this project is to bring innovations to mobile video delivery for new content types and over emerging networks. Specifically, the project investigates three aspects: (1) 360-degree immersive video delivery, (2) video streaming over multiple network paths (multipath), and (3) video streaming over millimeter-wave (mmWave) links. These are expected to be the key building blocks of next-generation video streaming services. First, 360-degree videos provide users with unique panoramic viewing experience; however, 360-degree video content delivery is much more challenging compared to regular videos. Second, multiple network interfaces have become a norm on off-the-shelf mobile devices but their potential is far from being fully exploited. Third, mmWave is a key technology that will be integrated into 5G wireless networks; but adapting video streaming to mmWave largely remains an uncharted territory. The proposed solutions will benefit the society by enhancing the user experience and reducing the resource consumption for next-generation immersive video services. The research will also be integrated with an education plan that seeks to prepare computer science students with the knowledge of new technological trends in networking and systems, and stimulate the general public interest in Science, Technology, Engineering, and Mathematics.

This project includes three inter-connected research thrusts. (1) For 360 video streaming, based on the concept of field-of-view (FoV) guided streaming, the project uses big data analytics to facilitate accurate head movement prediction, a key prerequisite for FoV-guided streaming. It also uses a rate adaptation scheme with a "delta encoding" design allowing the quality of a fetched chunk to be incrementally upgraded. This substantially improves adaptability when facing randomness in head movements. (2) For multipath streaming, the project uses multiple network interfaces to be used simultaneously for streaming videos. The network framework supports video rate adaptation and allows users to flexibly configure each path's cost. The framework also supports delay-sensitive live streaming over multipath through strategic packet scheduling. (3) mmWave links bear unique characteristics of massive capacity and intermittent availability. The project first designs a transport layer for mmWave links. It then proposes several video streaming strategies tailored to mmWave, such as strategically combining mmWave and legacy omni-directional radios. For the above research thrusts, the project will develop algorithms, models, and systems, backed up by real implementation and evaluation.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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