CAREER: Leveraging Context-Aware Sensing to Enhance QoE for Mobile Users: A Practical Framework Design

由于功能强大的移动终端的激增，视频流、视频通话和在线游戏等对资源要求很高的多媒体应用在过去十年中激增。如何提高终端用户主观上对这些应用的满意度，被广泛理解为体验质量，对于无线网络运营商来说至关重要。主流的QOE增强方法大多是面向运营商的，而用户扮演的角色有点有限。另一方面，移动设备配备了多个嵌入式传感器，能够收集和推断丰富的上下文信息。受这些观察结果的启发，该项目旨在利用以用户为中心的上下文感知来提高无线网络中的QOE。拟议的用户辅助服务质量改进如果成功，将有可能成为对现有服务质量中心管理框架的一个有希望的补充。此外，它还将开辟新的机会，纳入移动用户进行网络测量和管理，而这主要是由网络运营商单独进行的。该项目计划让女性和代表性不足的少数民族学生参与研究活动，并积极接触初中生和高中生。这一学术发现将广泛传播给社会。这个项目旨在开发一个实用的框架，利用上下文感知来提高QOE，并解决其中涉及的关键挑战。更具体地说，拟议的研究将通过三个密切相关的研究推进来进行。第一个推力研究基于从移动设备获取的历史记录的细粒度用户上下文预测。作为另一个关键因素，它进一步研究了如何利用预测结果来帮助无线网络中的资源供应和QOE改善。意识到上下文感知可能会导致额外的通信和能量开销，第二个推力旨在通过开发适应上下文动态的经济高效的上下文采样和精确重建来降低成本。第三个推力解决了上下文感知过程中的隐私问题。将开发一个灵活的上下文交易框架，允许个人用户决定在QOE改善交易中披露多少隐私。这项拟议的研究是跨学科的，涉及资源管理、学习技术、压缩感知、差异隐私和经济理论。建议的机制和设计将通过测量活动、模拟和实验研究相结合的方式进行彻底评估。将实施现成的移动设备、路由器、服务器和云的中型原型。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Due to the proliferation of powerful mobile terminals, resource-demanding multimedia applications, such as video streaming, video calls, and online gaming, have been surging during the past decade. How to improve the satisfaction of these applications as perceived subjectively by end-users, widely interpreted as the quality of experience (QoE), is critical to the operators of wireless networks. Prevailing QoE enhancement methods are mostly operator-oriented, while users play somewhat limited roles. On the other hand, mobile devices are equipped with multiple embedded sensors that enable the collection and inference of rich contextual information. Motivated by these observations, this project aims to leverage user-centric context sensing to enhance QoE in wireless networks. The proposed user-assisted QoE enhancement, if successful, has the potential to serve as a promising complement to the existing centralized QoE management framework. Besides, it will open up new opportunities that incorporate mobile users for network measurement and management that has been mostly conducted by network operators alone. The project plans to engage female and under-represented minority students in the research activities and actively outreach to middle and high school students. The scholarly discovery will be disseminated broadly to the community.This project intends to develop a practical framework to leverage context sensing for QoE enhancement and address critical challenges involved therein. More specifically, the proposed research will be carried out through three closely related research thrusts. The first thrust studies fine-granular user context prediction based on historical records harvested from mobile devices. As another key ingredient, it further investigates how to utilize the prediction results to assist with resource provisioning and QoE improvement in wireless networks. Realizing that context sensing may incur extra communication and energy overhead, the second thrust intends to reduce the cost by developing cost-efficient context sampling and accurate reconstruction that adapt to context dynamics. The third thrust addresses the privacy concern during context sensing. A flexible context trading framework will be developed to allow individual users to decide how much privacy to disclose in the trade of QoE improvement. The proposed research is inter-disciplinary, which spans resource management, learning techniques, compressive sensing, differential privacy, and economic theories. The proposed mechanisms and designs will be thoroughly evaluated via a combination of measurement campaigns, simulations, and experimental studies. A medium-scale prototype of off-the-shelf mobile devices, routers, servers, and cloud will be implemented.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.