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Optimizations and Economics of Multi...
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Tang, Ming.
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Optimizations and Economics of Multimedia Services.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Optimizations and Economics of Multimedia Services./
作者:
Tang, Ming.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:
225 p.
附註:
Source: Dissertations Abstracts International, Volume: 80-08, Section: B.
Contained By:
Dissertations Abstracts International80-08B.
標題:
Applied Mathematics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13837892
ISBN:
9780438851900
Optimizations and Economics of Multimedia Services.
Tang, Ming.
Optimizations and Economics of Multimedia Services.
- Ann Arbor : ProQuest Dissertations & Theses, 2018 - 225 p.
Source: Dissertations Abstracts International, Volume: 80-08, Section: B.
Thesis (Ph.D.)--The Chinese University of Hong Kong (Hong Kong), 2018.
This item must not be sold to any third party vendors.
With the fast development of communication and information technologies, humans have been increasingly enjoying multimedia services over the Internet. In order to better understand and provide such services, this thesis studies two important aspects of the multimedia over the Internet - multimedia service provision and multimedia platform operation. In the first part on the multimedia service provision, we study how to provide high quality-of-experience multimedia services. The study focuses on mobile network scenarios, which is quite challenging due to the heterogeneous and limited mobile device resources. To enhance the services, we propose crowdsourced resource sharing models that enable mobile users to form cooperative groups through device-to-device connections and share their resources for multimedia service provision. We start with communication resource sharing in a video streaming application scenario, where we propose a crowdsourced video streaming model that enables mobile users to share communication resources for video streaming downloading. Analyzing this model is challenging due to the asynchronous downloading behaviors of the video users and the private user information (e.g., their video buffer sizes). Overcoming the challenges, we design an online algorithm that approaches to the system theoretical best performance, and further design auction-based incentive mechanisms (to motivate user cooperation) that achieve truthful user information revelation and efficient resource allocation. We further study a joint communication, computation, and caching resources sharing in a general multimedia scenario, where we propose a joint sharing framework of three kinds of resources. The framework generalizes many existing mobile user resource sharing models, and it can offer more flexibilities in terms of device cooperation and resource scheduling. Under the general framework, we focus on a non-convex energy consumption minimization problem, and propose a linear programming heuristic resource allocation algorithm, which can produce an output that is empirically close to the optimal solution. In the second part on the multimedia platform operation, we study how the platform and users should behave on these platforms to maximize their payoffs. We focus on the emerging live streaming platforms, where streamers broadcast live streams for viewers. These platforms implement distinctive donation-based markets: streamers live stream free of charge, and viewers can voluntarily donate money to the streamers. The donations are split between the streamers and the platform with a fixed pre-agreed fraction. Under the donation-based markets, we study the platform's decision on the fixed split fraction design and streamers' decisions on their participations and service attribute selections (considering the preferences of streamers and viewers). To gain real-world insights, we further perform a case study based on the dataset collected from Twitch platform, and demonstrate how to compute the platform's optimal fraction without knowing the service attribute preferences of the streamers and viewers.
ISBN: 9780438851900Subjects--Topical Terms:
1669109
Applied Mathematics.
Optimizations and Economics of Multimedia Services.
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With the fast development of communication and information technologies, humans have been increasingly enjoying multimedia services over the Internet. In order to better understand and provide such services, this thesis studies two important aspects of the multimedia over the Internet - multimedia service provision and multimedia platform operation. In the first part on the multimedia service provision, we study how to provide high quality-of-experience multimedia services. The study focuses on mobile network scenarios, which is quite challenging due to the heterogeneous and limited mobile device resources. To enhance the services, we propose crowdsourced resource sharing models that enable mobile users to form cooperative groups through device-to-device connections and share their resources for multimedia service provision. We start with communication resource sharing in a video streaming application scenario, where we propose a crowdsourced video streaming model that enables mobile users to share communication resources for video streaming downloading. Analyzing this model is challenging due to the asynchronous downloading behaviors of the video users and the private user information (e.g., their video buffer sizes). Overcoming the challenges, we design an online algorithm that approaches to the system theoretical best performance, and further design auction-based incentive mechanisms (to motivate user cooperation) that achieve truthful user information revelation and efficient resource allocation. We further study a joint communication, computation, and caching resources sharing in a general multimedia scenario, where we propose a joint sharing framework of three kinds of resources. The framework generalizes many existing mobile user resource sharing models, and it can offer more flexibilities in terms of device cooperation and resource scheduling. Under the general framework, we focus on a non-convex energy consumption minimization problem, and propose a linear programming heuristic resource allocation algorithm, which can produce an output that is empirically close to the optimal solution. In the second part on the multimedia platform operation, we study how the platform and users should behave on these platforms to maximize their payoffs. We focus on the emerging live streaming platforms, where streamers broadcast live streams for viewers. These platforms implement distinctive donation-based markets: streamers live stream free of charge, and viewers can voluntarily donate money to the streamers. The donations are split between the streamers and the platform with a fixed pre-agreed fraction. Under the donation-based markets, we study the platform's decision on the fixed split fraction design and streamers' decisions on their participations and service attribute selections (considering the preferences of streamers and viewers). To gain real-world insights, we further perform a case study based on the dataset collected from Twitch platform, and demonstrate how to compute the platform's optimal fraction without knowing the service attribute preferences of the streamers and viewers.
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