NeTS: EAGER: Exploring Smart Media Pricing In QoE-Driven Network Economics To Revitalize Wireless Multimedia Resource Allocation

NetS：EAGER：探索 QoE 驱动的网络经济中的智能媒体定价，以振兴无线多媒体资源分配

• 批准号: 1744182
• 负责人: Wei Wang
• 金额: $ 10万
• 依托单位: San Diego State University Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1744182&HistoricalAwards=false
• 关键词: NeTS; EAGER; Exploring; Smart; Media

The global internet traffic is aggressively increasing at an enormous rate, posing significant challenges to modern network protocol design. In addition, multimedia has become the "biggest big data" running through the last mile of wireless access networks, such as video on demand, cloud-based video games, and social media video sharing. This project explores potential solutions to support such big volumes of multimedia traffic over resource-constrained wireless access networks. In particular, this project investigates new approaches to improve quality of experience (QoE) for multimedia users by employing high level economic theories, orchestrating low level communication resources, and exploring selfish user behaviors among neighboring devices.The goal of this project is to test the hypothesis that the wireless big data multimedia communication challenge could be partially solved by leveraging a new concept of smart media pricing to transform the wireless resource allocation from rate-distortion fashion to price-distortion fashion. This project pursues two coherent thrusts beyond traditional resource allocation: (1) creating a non-uniform quality-driven smart multimedia pricing model to assign different prices to multimedia packet groups with different quality contributions and decoding influences, and thus leveraging price as a new dimension in resource allocation; (2) designing a profit-driven cache delegation protocol to improve multimedia quality through offloading, and thus encouraging users to scavenge recently cached media contents from neighboring devices. The models, algorithms and protocols developed through this project could possibly identify new frontiers of pricing policy design in wireless multimedia resource allocation research. Research findings will be integrated to education curriculum and student advising, to broaden students' future career potentials and contribute to the U.S. workforce preparation.

全球互联网流量以巨大的速度积极增加，对现代网络协议设计构成了重大挑战。此外，多媒体已成为通过无线访问网络的最后一英里（例如视频按需，基于云的视频游戏和社交媒体视频共享）运行的“最大大数据”。该项目探讨了潜在的解决方案，以支持资源约束的无线访问网络，支持大量的多媒体流量。特别是，该项目通过采用高级经济理论，策划低水平的沟通资源并探索邻近设备之间的自私用户行为，调查新方法来改善多媒体用户的经验质量（QOE）。该项目的目的是测试以下假设，即在实现智能范围的情况下，可以通过将智能媒体纳入智能的范围，以使人的无线大数据跨度能够逐步解决，以使其成为智能的范围，从而使媒体构成良好的范围。价格延伸时尚。该项目追求两个连贯的推力超出传统资源分配：（1）创建一个非统一质量驱动的智能多媒体定价模型，以将不同的价格分配给具有不同质量贡献和解码影响的多媒体数据包组，从而利用价格为资源分配的新维度； （2）设计一种以利润为驱动的高速缓存委托协议来通过卸载来提高多媒体质量，从而鼓励用户清除最近从相邻设备中缓存媒体内容。通过该项目开发的模型，算法和协议可能可以确定无线多媒体资源分配研究中定价策略设计的新边界。研究结果将纳入教育课程和学生建议，以扩大学生的未来职业潜力，并为美国的劳动力准备做出贡献。

项目成果

A Generalized Best-Response Smart Media Pricing Economic Model for Wireless Multimedia Communications

• DOI: 10.1109/ccnc.2019.8651680
• 发表时间: 2019
• 期刊: 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)
• 作者: Shuan He;Wei Wang

Price the QoE, Not the Data: SMP-Economic Resource Allocation in Wireless Multimedia Internet of Things

• DOI: 10.1109/mcom.2018.1701219
• 发表时间: 2018-09-01
• 期刊: IEEE COMMUNICATIONS MAGAZINE
• 影响因子: 11.2
• 作者: Wang, Wei;Wang, Qin
• 通讯作者: Wang, Qin

Pricing QoE With Reinforcement Learning For Intelligent Wireless Multimedia Communications

• DOI: 10.1109/icc40277.2020.9149429
• 发表时间: 2020-01-01
• 期刊: ICC 2020 - 2020 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC)
• 作者: He, Shuan;Wang, Wei
• 通讯作者: Wang, Wei

Prospect Theoretic Pricing For QoE Modeling In Wireless Multimedia Networking

无线多媒体网络中 QoE 建模的前景理论定价

• DOI: 10.1109/ietc47856.2020.9249205
• 发表时间: 2020
• 期刊: Technology and Computing (IETC
• 作者: Kattiyan Ramamoorthy, Krishna M.;Wang, Wei
• 通讯作者: Wang, Wei

Profit-Driven Cache Delegation: A Game-Theoretic Wireless Multimedia Offloading Solution

• DOI: 10.1109/icc42927.2021.9500995
• 发表时间: 2021-06
• 期刊: ICC 2021 - IEEE International Conference on Communications
• 作者: K. Ramamoorthy;Wei Wang