A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities
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DOI：
10.1109/comst.2019.2914030
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发表时间：
2019-01-01
影响因子：
35.6
通讯作者：
Bouvry, Pascal
中科院分区：
文献类型：
--
作者：
Capponi, Andrea;Fiandrino, Claudio;Bouvry, Pascal
近年来，立方体卫星以其相对较低的成本和较快的开发周期吸引了越来越多的学术界的兴趣。与所有自主航天器一样，立方体卫星依靠与地面站的无线电通信来接收执行科学任务的命令，并将遥测和测量数据传回地球进行处理。本文讨论了计划于2019年作为弗吉尼亚立方体卫星星座(VCC)项目的一部分发射的老道明大学(ODU)立方体卫星通信系统的无线电链路设计。报告包括系统的概述和射频链路预算分析，以及重要的设计方面，包括立方体卫星无线电的阻抗匹配，地面站无线电的定制接口，以及所使用的链路层协议的概述。移动人群传感(MCS)近年来得到了极大的关注，并已成为城市传感的一个有吸引力的范例。对于数据的收集，MCS系统依赖于大量参与者或人群的移动设备的贡献。智能手机、平板电脑和可穿戴设备被广泛部署，并已配备了丰富的传感器集，使它们成为极好的信息来源。与传统的传感器网络相比，人类的移动性和智能性保证了更高的覆盖率和更好的上下文感知。与此同时，出于隐私方面的考虑，个人可能不愿分享数据。出于这个原因，MCS框架专门设计为包括激励机制和解决隐私问题。尽管研究界的兴趣与日俱增，但MCS解决方案需要在从传感和通信到系统管理和数据存储的许多方面进行更深入的调查和分类。在本文中，我们进一步研究了MCS，对该领域现有的工作进行了综述，并提出了一个详细的分类方法，以阐明当前的情况并对应用程序、方法和体系结构进行分类。我们的目标不仅是分析和巩固过去的研究，而且还概述了潜在的未来研究方向以及与其他研究领域的协同作用。
CubeSats have attracted increased interest from the academic community in recent years due to their relative low cost and rapid development cycle. As is the case with all autonomous spacecraft, CubeSats rely on radio communications with ground stations to receive commands for performing scientific missions, and to transmit telemetry and measurement data back to Earth for processing. This paper discusses the radio link design for the Old Dominion University (ODU) CubeSat communication system that is scheduled to be launched in 2019 as part of the Virginia CubeSat Constellation (VCC) project. The presentation includes an overview of the system and the RF link budget analysis, along with salient design aspects including impedance matching for the CubeSat radio, a custom interface for the ground station radio, and an outline of the link layer protocol used.Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing. For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd. Smartphones, tablets, and wearable devices are deployed widely and already equipped with a rich set of sensors, making them an excellent source of information. Mobility and intelligence of humans guarantee higher coverage and better context awareness if compared to traditional sensor networks. At the same time, individuals may be reluctant to share data for privacy concerns. For this reason, MCS frameworks are specifically designed to include incentive mechanisms and address privacy concerns. Despite the growing interest in the research community, MCS solutions need a deeper investigation and categorization on many aspects that span from sensing and communication to system management and data storage. In this paper, we take the research on MCS a step further by presenting a survey on existing works in the domain and propose a detailed taxonomy to shed light on the current landscape and classify applications, methodologies, and architectures. Our objective is not only to analyze and consolidate past research but also to outline potential future research directions and synergies with other research areas.