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

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，它可以持续监测大量道路上的车辆的状态，以及明智地规划智能交通系统，将交通拥堵和废气排放降至最低。虽然车辆的短程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，由于它们的中央处理单元(CPU)能力有限，它们无法以在线方式高效地处理数据。然而，云计算平台最擅长的是繁重的计算。可以通过众包的方式收集大量的车辆数据，如位置、速度、加速度、瞬时里程和发动机状态，以便在云中进行处理。

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.