An Exchange Market Approach for Mobile Crowdsensing

移动群智感知的交易市场方法

• 批准号: 1408409
• 负责人: Junshan Zhang
• 金额: $ 35万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1408409&HistoricalAwards=false
• 关键词: Exchange; Market; Approach; Mobile; Crowdsensing

Small-sized portable mobile devices, including smartphones and tablet computers, are becoming extremely prevailing. These pocket-sized gadgets have a set of embedded sensors and can provide abundant sensing data about the environment and human society, thus offering great opportunities to carry out crowdsensing. One primary objective of this project is to develop a mobile crowdsensing framework with fair pricing and task allocation. A key challenge is that different parties involved in mobile crowdsensing, including mobile users, task owners, and the platform, have conflicting interests: 1) mobile users aim to maximize the profit for performing sensing tasks; 2) task owners strive to get their sensing tasks performed with high quality of sensing, at a cost as small as possible; and 3) the platform would desire social welfare maximization. Based on recent advances in Exchange Economy theory, this project will tackle this challenge to strike a right balance and enable them to work in concert. This project serves as an excellent example for exploring innovative research on the interplay among engineering, economics and operation research. It will spur a new line of thinking for large-scale mobile sensing in applications including smart health and smart city, benefiting the society at large. Another major task of this project is to integrate research into educational activities.Appealing to Exchange Economy theory, this project employs the notion of "Walrasian Equilibrium" as the overall metric, at which there exists a price vector for mobile users and an allocation for task owners, such that the allocation is Pareto optimal and the market gets cleared (i.e., all sensing tasks are performed). Under the common theme of joint pricing and task scheduling with constraints, this project is centered around devising algorithms that can achieve a Walrasian Equilibrium, for both cases where sensing tasks are either divisible or indivisible. Thrust I studies joint pricing and task allocation for crowdsensing with divisible sensing tasks, via a strategic bargaining approach. The existence of a Walrasian Equilibrium will be investigated first, together with a centralized scheme used as a benchmark. Then, based on multi-lateral bargaining theory, decentralized algorithms will be devised where mobile users and task owners negotiate with each other to determine the pricing and allocation, and the convergence of the bargaining game output to a Walrasian Equilibrium will be investigated thoroughly. Thrust II will be devoted to joint pricing and allocation for crowdsensing with indivisible sensing tasks. One challenge in this more sophisticated setting is that there may not exist a Walrasian Equilibrium. In light of this, the notion of Combinatorial Walrasian Equilibrium (a relaxation of Walrasian Equilibrium) will be applied to characterize an "optimal state." Since this relaxation may give rise to some inefficiency issues, the Tatonnement based approach will be taken to quantify the corresponding performance, in terms of the ratios to approximate the optimal social welfare and individual revenue. Further, decentralized solutions will be developed to achieve a Combinatorial Walrasian Equilibrium.

小型便携式移动设备（包括智能手机和平板电脑）变得极为普遍。这些口袋大小的小工具具有一组嵌入式传感器，可以提供有关环境和人类社会的大量传感数据，从而提供了巨大的机会来进行人群。 该项目的主要目标是通过公平的定价和任务分配来开发移动人群框架。一个关键的挑战是，包括移动用户，任务所有者和平台在内的移动人拥挤的不同各方具有相互矛盾的利益：1）移动用户旨在最大程度地利用执行传感任务的利润； 2）任务所有者努力以高质量的传感执行其传感任务，以尽可能小； 3）平台将希望社会福利最大化。根据交换经济理论的最新进展，该项目将应对这一挑战以实现正确的平衡并使他们能够协同工作。该项目是探索有关工程，经济学和运营研究之间相互作用的创新研究的一个很好的例子。它将刺激在包括智能健康和智慧城市在内的应用程序中进行大规模移动感知的新思路，从而使整个社会受益。该项目的另一个主要任务是将研究整合到教育活动中。介绍交换经济理论，该项目采用“ Walrasian equilibrium”的概念作为整体指标，在该指标上，在该指标上，在其中，在该指标上，有移动用户的价格向量和任务所有者的分配价格，因此分配是PARETO OPTINAL，并且市场是PARETO的，并且市场已清除（即清除（即所有感知的任务））。在与限制的共同定价和任务调度的共同主题下，该项目的重点是设计可以达到Walrasian均衡的算法，对于这两种情况下，感应任务都是可划分或不可分割的情况。推力I研究通过战略谈判方法来研究与可分配的感应任务的联合定价和任务分配。 Walrasian平衡的存在将首先研究，并将其用于基准的集中式方案。然后，基于多边讨价还价理论，将设计分散的算法，其中移动用户和任务主相互谈判以确定定价和分配，以及讨价还价的游戏输出与沃尔拉斯均衡的融合。推力II将致力于与不可分割的感应任务进行人群的联合定价和分配。在这种更复杂的环境中，一个挑战是可能不存在沃拉斯平衡。鉴于这种情况，将使用组合沃拉斯平衡的概念（沃拉斯平衡的松弛）来表征“最佳状态”。由于这种放松可能导致一些效率低下的问题，因此将采用基于Tatonnement的方法来量化相应的绩效，以近似最佳的社会福利和个人收入。此外，将开发分散的解决方案，以达到组合沃拉斯平衡。