A cloud-assisted crowdsourcing machine-to-machine networking platform for vehicular applications

用于车辆应用的云辅助众包机器对机器网络平台

• 批准号: 447493-2013
• 负责人: Li, Baochun
• 金额: $ 10.96万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=575321
• 关键词: cloud; assisted; crowdsourcing; machine; networking

Machine-to-Machine (M2M) networks have recently attracted significant attention from both industry and academia. Prominent examples are vehicular communication networks, which enable continuous status monitoring of a massive number of on-road vehicles, as well as smart planning towards an intelligent transport system with minimized traffic congestion and exhaust gas emission. Though vehicles are increasingly capable of both short-range and broadband cellular access, they still have limited communication bandwidth and opportunities. Further, due to their limited Central Processing Unit (CPU) power, they are not able to process data efficiently in an online fashion. Heavy-lifting computation, however, is where cloud computing platforms excel. Large volumes of vehicular data, such as location, speed, acceleration, instantaneous mileage and engine status, can be collected in a crowdsourcing fashion, such that they can be processed in the cloud. This proposed Strategic Project seeks to design and implement an efficient crowdsourcing M2M networking platform with full cloud integration, with a specific focus on the integration of vehicular networks. From a theoretical perspective, one original highlight of this project is to study the combination of coding techniques and storage capabilities of both vehicular and road-side communicating nodes, so that a variety of delay constraints can be accommodated as we maximize information flow rates in vehicular applications. From a practical perspective, our new platform will assist rapid development of a new array of applications based on the results of processing crowdsourced data. The proposed research in this project will be undertaken in close collaboration with two industry partners: Qualcomm Canada a world-renowned innovator in wireless communication technologies; and moj.io, a start-up company specializing in cloud applications for vehicular networks.

机器对机器（M2M）网络最近引起了工业界和学术界的极大关注。 突出的例子是车辆通信网络，它可以对大量道路车辆进行连续状态监控，以及对智能交通系统进行智能规划，最大限度地减少交通拥堵和废气排放。 尽管车辆的短距离和宽带蜂窝接入能力越来越强，但它们的通信带宽和机会仍然有限。此外，由于中央处理单元（CPU）能力有限，它们无法以在线方式有效地处理数据。然而，繁重的计算才是云计算平台的优势所在。可以通过众包方式收集大量车辆数据，例如位置、速度、加速度、瞬时里程和发动机状态，以便在云端进行处理。 该拟议战略项目旨在设计和实施一个具有完全云集成的高效众包 M2M 网络平台，特别关注车辆的集成 网络。 从理论角度来看，该项目的一个原创亮点是研究车辆和路侧通信节点的编码技术和存储能力的结合，以便在车辆应用中最大化信息流率的同时可以适应各种延迟约束。从实践的角度来看，我们的新平台将有助于基于众包数据处理结果快速开发一系列新的应用程序。 该项目拟议的研究将与两个行业合作伙伴密切合作进行：高通加拿大公司，世界知名的无线通信技术创新者； moj.io是一家专门从事车载网络云应用的初创公司。