Grant: Discovery Grants Program - Individual
Simon Fraser University
$148,000.00
Towards Highly Interactive Networked Multimedia Services with Crowd Intelligence
FY 2023-24
Summary
With the advances in social, mobile and cloud computing, crowdsourcing has become the norm in today's digital media production and sharing, which utilizes the collective effort of users in the online community. With no doubt, networked services in the future will focus on the user experience and participation with rich media from the crowd. The boundless coverage of socialized media sharing however presents unprecedented scale challenges. Highly diversified content types, origins, and distribution channels further impose complex interactions among the individual participants, particularly for advanced immersive applications such as interactive livecast/gamecast, multi-party media production, online gaming and augmented reality (AR). Their demands on quality and responsiveness are much higher (e.g., latency in the order of 100 ms, or even 10 ms for AR) than conventional IPTV or VoIP. These rich interactions, on the other hand, provide rich and low cost data that were previously unavailable. Leveraging advanced data analytics and learning tools, the hidden intelligence from the crowd can be unveiled toward better system design. For instance, inferring game progress from live chat messages and tracking viewport through gaze patterns for resource reservation and display optimization. Yet uncalibrated data in the wild can be highly noisy, not to mention the intrinsic heterogeneity and dynamics of the Internet. Our research is guided by the following critical question: How can massive digital media content be effectively generated and delivered among the crowd with intensive online interactions and with the intelligence therein? Our long-term objective is to systematically examine the challenges in advanced interactive and crowdsourced multimedia services and to develop integrated solutions that will accommodate and utilize the interactions. A series of issues are to be addressed within the solution framework: (1) Online analysis of crowdsourced interaction data; (2) Advanced computing and communication architecture, in particular, cloud-edge collaboration for delay-sensitive applications; (3) Ultra-low-latency and -energy data transport. Beyond simply putting the individual results together, the design of individual modules will be revisited during system integration. This iterative process will eventually lead to an optimized coherent design, making the future multimedia services agile, efficient, and intelligent, and, in the long run, benefiting emerging applications without human-in-the-loop, such as assisted/autonomous driving. My team's broad expertise with state-of-the-art computing and communication systems has prepared us for exploring these new research frontiers. We will train highly qualified personnel and will nurture extensive collaboration with academic researchers worldwide, as well as with local and international industrial partners to pursue technology transfers, so as to raise Canada's global profile in this priority area.
Program
Discovery Grants Program - Individual
Recipient
Location
British Columbia, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RGPIN-2019-04040
Name nom
Liu, Jiangchuan
Department département
Computing Science, School of - Computing Science, School of
Organization id
5
Institution établissement
Simon Fraser University
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2019
Award amount
148000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
803
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer communications
Area of application fr
Téléinformatique
Research subject code
9999
Research subject group en
Not available
Research subject group fr
Not available
Research subject en
Non disponible
Research subject fr
Non disponible
Application title
Towards Highly Interactive Networked Multimedia Services with Crowd Intelligence
Keyword
Cloud computing; Content distribution; Crowdsourcing; Edge computing; Internet; Machine intelligence; Mobile computing; Multimedia communication; User interaction; Video streaming
Application summary
With the advances in social, mobile and cloud computing, crowdsourcing has become the norm in today's digital media production and sharing, which utilizes the collective effort of users in the online community. With no doubt, networked services in the future will focus on the user experience and participation with rich media from the crowd. The boundless coverage of socialized media sharing however presents unprecedented scale challenges. Highly diversified content types, origins, and distribution channels further impose complex interactions among the individual participants, particularly for advanced immersive applications such as interactive livecast/gamecast, multi-party media production, online gaming and augmented reality (AR). Their demands on quality and responsiveness are much higher (e.g., latency in the order of 100 ms, or even 10 ms for AR) than conventional IPTV or VoIP. These rich interactions, on the other hand, provide rich and low cost data that were previously unavailable. Leveraging advanced data analytics and learning tools, the hidden intelligence from the crowd can be unveiled toward better system design. For instance, inferring game progress from live chat messages and tracking viewport through gaze patterns for resource reservation and display optimization. Yet uncalibrated data in the wild can be highly noisy, not to mention the intrinsic heterogeneity and dynamics of the Internet. Our research is guided by the following critical question: How can massive digital media content be effectively generated and delivered among the crowd with intensive online interactions and with the intelligence therein? Our long-term objective is to systematically examine the challenges in advanced interactive and crowdsourced multimedia services and to develop integrated solutions that will accommodate and utilize the interactions. A series of issues are to be addressed within the solution framework: (1) Online analysis of crowdsourced interaction data; (2) Advanced computing and communication architecture, in particular, cloud-edge collaboration for delay-sensitive applications; (3) Ultra-low-latency and -energy data transport. Beyond simply putting the individual results together, the design of individual modules will be revisited during system integration. This iterative process will eventually lead to an optimized coherent design, making the future multimedia services agile, efficient, and intelligent, and, in the long run, benefiting emerging applications without human-in-the-loop, such as assisted/autonomous driving. My team's broad expertise with state-of-the-art computing and communication systems has prepared us for exploring these new research frontiers. We will train highly qualified personnel and will nurture extensive collaboration with academic researchers worldwide, as well as with local and international industrial partners to pursue technology transfers, so as to raise Canada's global profile in this priority area.