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.

包括智能手机和平板电脑在内的小型便携式移动设备正在变得非常流行。这些口袋大小的设备内置了一组传感器，可以提供丰富的环境和人类社会的传感数据，从而为开展群智感知提供了绝佳的机会。 该项目的一个主要目标是开发一个具有公平定价和任务分配的移动众感知框架。一个关键的挑战是移动众感知的不同参与方，包括移动用户、任务所有者和平台，存在利益冲突：1）移动用户的目标是执行感知任务的利润最大化； 2）任务负责人努力以尽可能小的成本，以高质量的传感来执行其传感任务； 3）平台希望社会福利最大化。基于交换经济理论的最新进展，该项目将应对这一挑战，以实现适当的平衡并使它们能够协同工作。该项目是探索工程、经济学和运筹学之间相互作用的创新研究的一个很好的例子。它将激发大规模移动传感在智慧健康和智慧城市等应用中的新思路，造福整个社会。该项目的另一个主要任务是将研究融入教育活动中。该项目借鉴交换经济理论，采用“瓦尔拉斯均衡”的概念作为总体衡量标准，其中存在移动用户的价格向量和任务分配所有者，这样分配是帕累托最优的并且市场被清理（即，所有传感任务都被执行）。在联合定价和带约束的任务调度的共同主题下，该项目的重点是设计可以实现瓦尔拉斯均衡的算法，适用于传感任务可分割或不可分割的两种情况。 Thrust I 通过战略讨价还价方法研究具有可分割感知任务的众感知的联合定价和任务分配。首先将研究瓦尔拉斯均衡的存在性，以及用作基准的集中方案。然后，基于多边讨价还价理论，设计去中心化算法，让移动用户和任务所有者相互协商确定定价和分配，并深入研究讨价还价博弈输出向瓦尔拉斯均衡的收敛性。 Thrust II 将致力于对具有不可分割的传感任务的众感知进行联合定价和分配。在这种更复杂的环境中，一个挑战是可能不存在瓦尔拉斯均衡。鉴于此，组合瓦尔拉斯均衡（瓦尔拉斯均衡的松弛）的概念将被应用于表征“最佳状态”。由于这种放松可能会引起一些低效率的问题，因此将采用基于Tatonnement的方法来量化相应的绩效，以近似最佳社会福利和个人收入的比率。此外，将开发去中心化解决方案以实现组合瓦尔拉斯均衡。