Participation and reporting in participatory sensing

M. Cheung, Fen Hou, Jianwei Huang
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引用次数: 9

Abstract

In participatory sensing (PS), users use smartphones to collect information related to a certain phenomenon of interest, and report their sensed data to the service provider through cellular or Wi-Fi networks. Previous studies on the incentive mechanism design for user participation often neglect the details of data reporting, which is non-trivial given the user mobility, location-dependent network availability, and transmission cost. In this paper, we study the decisions of the service provider and the users in PS applications that involve photo or video transmissions, where the reporting cost through the cellular network is non-negligible. The service provider uses a deadline reward scheme to motivate users to participate, and optimizes its reward to maximize its expected surplus. Users make their participation and reporting decisions based on the reward announced by the service provider. We jointly consider the user mobility and multiple access methods with different transmission costs and location heterogeneity in the problem formulation and analysis. For the general case with a time-discounted reward, we formulate a user's reporting decision problem as a sequential decision problem, and propose an optimal participation and reporting decisions (OPRD) algorithm using dynamic programming. For the special case with a fixed reward, we derive the closed-form participation and reporting decisions. Simulation results show that the OPRD algorithm improves the user payoff over the patient and impatient schemes by 9.8% and 13.2%, respectively.
参与式感知中的参与与报告
在参与式感知(PS)中,用户使用智能手机收集与某个感兴趣的现象相关的信息,并通过蜂窝网络或Wi-Fi网络将其感知到的数据报告给服务提供商。以往关于用户参与激励机制设计的研究往往忽略了数据报告的细节,考虑到用户的移动性、位置相关的网络可用性和传输成本,这是非常重要的。在本文中,我们研究了PS应用中涉及照片或视频传输的服务提供商和用户的决策,其中通过蜂窝网络的报告成本是不可忽略的。服务提供商使用最后期限奖励方案来激励用户参与,并对其奖励进行优化,使其预期盈余最大化。用户根据服务提供商公布的奖励做出参与和报告决策。在问题的制定和分析中,我们综合考虑了用户移动性、不同传输成本的多址方式和位置异质性。对于具有时间折扣奖励的一般情况,我们将用户的报告决策问题表述为顺序决策问题,并提出了一种基于动态规划的最优参与和报告决策(OPRD)算法。对于具有固定报酬的特殊情况,我们导出了封闭式的参与和报告决策。仿真结果表明,OPRD算法比耐心方案和不耐烦方案分别提高了9.8%和13.2%的用户收益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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