NeTS: Small: Enabling High-Quality Mobile Crowdsourcing with Lifestyle-aware and Energy-efficient Control

众包应用的成功与否，在很大程度上取决于能否招募到有能力的人群来承担相应的任务。对于大多数应用程序来说，成本也是一个很大的问题。最近的研究一直集中在移动的众包的激励机制，决定如何招募人群主要是基于他们的价格/成本。然而，很少注意被招募人群的能力，即，每个单独的移动的用户和整个群体潜在地能够提供的服务/数据的质量。该项目团队旨在为移动的众包设计一种新的生活方式感知方法。基本思想是保持一组（相对）稳定的移动的用户，并学会全面了解他们的生活模式（即，这项研究将显著提高移动的众包服务的质量，降低移动众包服务的能耗，对移动的众包服务提供商和用户都有好处，更重要的是对全球环境也有好处。此外，拟议的项目预计将填补文献空白，并激发更多的研究沿着这条线。该项目的目标，使高质量的移动的众包，通过设计一种新颖的和整体的解决方案，为人群招募，它利用一个节能的框架，通过智能手机传感学习的生活方式的移动的用户，然后采用生活方式感知算法和激励机制，人群招募。为了实现上述目标，拟议的研究分为三个有凝聚力的研究重点：重点1节能生活方式学习：将开发一个统一的节能框架，通过描述移动的用户的行为和习惯，并预测他们未来的活动来学习他们的生活方式;重点2生活方式感知人群招募和激励机制：将开发人群质量（QoC）模型和生活方式感知算法，以实现有效的人群招募;推进3实施和性能评估：所提出的方法将在智能手机传感平台上实施，并将通过广泛的模拟和实验进行验证和评估。

The success of a crowdsourcing application highly depends on whether a capable crowd can be recruited to undertake the corresponding tasks. For most applications, the cost is also a big concern. Recent research has been focused on incentive mechanisms for mobile crowdsourcing, which determine how to recruit a crowd mainly based on their prices/costs. However, scant attention has been paid to capability of the recruited crowd, i.e., the quality of services/data each individual mobile user and the whole crowd are potentially capable of providing. The project team aims to design a new lifestyle-aware approach for mobile crowdsourcing. The basic idea is to maintain a (relatively) stable set of mobile users and learn to gain a comprehensive view of their life patterns (i.e., their capabilities) such that once a mobile crowdsourcing task is received, a good crowd, whose capabilities well match the task, can be quickly found. The proposed research will significantly improve quality of mobile crowdsourcing services and reduce their energy usages, which can substantially benefit mobile crowdsourcing service providers and users, and more importantly, is good for global environment. Moreover, the proposed project is expected to fill the literature gap and inspire more research along this line.The objective of this project to enable high-quality mobile crowdsourcing by designing a novel and holistic solution for crowd recruitment, which utilizes an energy-efficient framework for learning lifestyles of mobile users via smartphone sensing, and then employs lifestyle-aware algorithms and incentive mechanisms for crowd recruitment. To achieve the above objective, the proposed research is organized into three cohesive research thrusts: Thrust 1 Energy-efficient Lifestyle Learning: a unified and energy-efficient framework will be developed to learn lifestyles of mobile users by characterizing their behaviors and habits, and predicting their future activities; Thrust 2 Lifestyle-aware Crowd Recruitment and Incentive Mechanisms: Quality of Crowd (QoC) models and lifestyle-aware algorithms will be developed for effective crowd recruitment; Thrust 3 Implementation and Performance Evaluation: the proposed approaches will be implemented on a smartphone sensing platform and will be validated and evaluated via extensive simulation and experiments.