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，它可以对大量道路车辆进行连续状态监测，并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。 虽然车辆越来越能够进行短距离和宽带蜂窝接入，但它们的通信带宽和机会仍然有限。此外，由于其有限的中央处理单元（CPU）功率，它们无法以在线方式有效地处理数据。然而，云计算平台在繁重的计算方面表现出色。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，可以以众包的方式收集，以便它们可以在云中处理。

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.