Mobile Vehicular Cloud

随着无线技术的进步，车载网络支持广泛的新型安全和信息娱乐服务，例如紧急通知、防撞、车队管理和多媒体内容共享。虽然，车辆网络研究在许多研究方向（例如，新的广播和路由协议），很少关注嵌入在车辆中的大量计算、通信、感测和存储资源，如果在用户之间共享这些资源，则可以产生在车辆本身中托管的车辆服务。在这个项目中，我们提出了一种新的车辆云架构，支持广泛的服务提供的移动的以及固定车辆在分布式方式，这些服务包括网络作为一个服务，存储作为一个服务，传感作为一个服务，计算智能作为一个服务和位置信息和密度估计作为一个服务。为了有效地支持车辆云服务，我们的目标是开发优化模型来计算最优/接近最优的配置车辆云，满足一定的QoS存在的几个约束条件;鉴于这些问题的复杂性，我们将采取启发式/元启发式方法来解决由此产生的模型。 此外，我们会发展新的管理技术，以有效地利用带宽，减少延迟的可靠传输，减少连接中断和有效的车辆密度信息传输。

With the advancement of wireless technologies, vehicular networks support a wide spectrum of novel safety and infotainment services, such as emergency notification, collision avoidance, fleet management, and multimedia content sharing. Although, vehicular network research resulted in several key contributions in multitude of research directions (e.g., novel broadcast and routing protocols), little attention has been paid towards the abundance of computing, communication, sensing and storage resources embedded in vehicles, which if shared among users can give rise to vehicular services hosted in the vehicles themselves. In this project, we propose a novel vehicular cloud architecture that supports a wide range of services provided by mobile as well as stationary vehicles in a distributed manner; these services include Network as a Service, Storage as a Service, Sensing as a Service, Computational Intelligence as a Service and Location Information and Density Estimation-as-a-Service. For efficient support of vehicular cloud services, we aim at developing optimization models to compute optimal/near optimal configurations of vehicular cloud that satisfy certain QoS in presence of several constraints; given the complexity of these problems we will resort to heuristic/meta-heuristic approaches to solve the resulting models. In addition, we will develop novel management techniques for efficient bandwidth utilization, reliable transfer with reduced delay, lesser connections disruption and efficient vehicular density information transfer.