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A cluster-based approach to cooperative mobile crowd monitoring

基于集群的协作移动人群监测方法

基本信息

批准号：
275521334
负责人：
Dr. Christin Groba
金额：
--
依托单位：
Professur für Rechnernetze
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2015
资助国家：
德国
起止时间：
2014-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/275521334?language=en
关键词：
cluster based approach cooperative mobile

项目摘要

Knowing where crowds of people emerge is essential for many applications, e.g., to efficiently manage resources like emergency response personnel, volunteers, or public transport. Mobile phone sensing may be an inexpensive and flexible way to obtain real-time crowd information as it lets the community collect sensor data with their mobile phones where otherwise dedicated sensing infrastructure needs to be deployed. However, non-cooperative approaches where individuals frequently upload sensor data to a distant server strain the network infrastructure and the battery of the participating phones. This leads to frustration, less participation, and reduced information accuracy.Research on peer-to-peer and wireless sensor networks has addressed traffic off-loading and energy conservation with cooperative concepts like device-to-device communication, decentralised node clustering, job rotation, duty cycling, and distributed sensing. It is, however, unclear: 1) how suitable these concepts are when applied to mobile crowd monitoring, 2) how these concepts integrate with each other on mobile phones, and 3) what their impact is when collectively applied. Cooperative mobile phone sensing, where individuals network and bundle their data, has only started to emerge and current approaches addresses these research questions only partially. In particular, existing solutions are designed for small-scale cooperation, are not yet adaptive to the dynamics of the crowd, or do not study the effect of multiple concepts simultaneously. This project will investigate the research questions by iteratively analysing the costs and benefits of different clustering and energy conservation techniques on mobile phones, large-scale simulated ad hoc networks, and in real crowd scenes. It will develop Conic, an energy-efficient and adaptive clustering scheme for cooperative mobile crowd monitoring. With the resulting prototype and quantitative data, the project hopes to contribute to a better understanding of how a crowd of people can be monitored with a transient network of energy-constrained mobile phones. Further, it hopes to provide researchers and practitioners with evidence to support their decision on a viable approach for mobile sensing applications. In the long run, the project will establish the basis for further research in crowd-based sensing and its integration into smart city concepts.

了解人群出现的位置对于许多应用至关重要，例如，有效管理应急响应人员、志愿者或公共交通等资源。移动的电话感测可以是获得实时人群信息的廉价且灵活的方式，因为它允许社区在需要部署专用感测基础设施的情况下用他们的移动的电话收集传感器数据。然而，个人频繁地将传感器数据上传到远程服务器的非合作方法使网络基础设施和参与手机的电池紧张。对等和无线传感器网络的研究已经解决了流量卸载和节能与合作的概念，如设备到设备的通信，分散的节点集群，工作轮换，责任循环和分布式传感。然而，目前尚不清楚：1）这些概念在应用于移动的人群监控时有多合适，2）这些概念如何在移动的电话上彼此集成，以及3）当共同应用时它们的影响是什么。合作的移动的电话传感，其中个人网络和捆绑他们的数据，才刚刚开始出现，目前的方法解决这些研究问题只有部分。特别是，现有的解决方案是专为小规模的合作，还没有适应人群的动态，或不研究多个概念的影响，同时。这个项目将调查的研究问题，通过迭代分析的成本和效益不同的集群和节能技术在移动的电话，大规模的模拟ad hoc网络，并在真实的人群场景。它将开发Conic，这是一种用于合作移动的人群监测的节能和自适应聚类方案。该项目希望通过由此产生的原型和定量数据，有助于更好地了解如何通过能量受限的移动的电话的瞬态网络来监控人群。此外，它希望为研究人员和从业人员提供证据，以支持他们对移动的传感应用的可行方法的决定。从长远来看，该项目将为进一步研究基于人群的感知及其融入智慧城市概念奠定基础。