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，如紧急通知、避免碰撞、车队管理和多媒体内容共享。尽管车载网络研究在许多研究方向（例如，新颖的广播和路由协议）上做出了一些关键贡献，但很少有人关注嵌入在车辆中的丰富的计算、通信、传感和存储资源，如果这些资源在用户之间共享，就可以产生托管在车辆本身的车辆服务。在这个项目中，我们提出了一种新的车辆云架构，该架构以分布式的方式支持移动和固定车辆提供的广泛服务；这些服务包括网络即服务、存储即服务、传感即服务、计算智能即服务以及位置信息和密度估计即服务。为了有效地支持车载云服务，我们旨在开发优化模型，以计算在存在若干约束的情况下满足一定QoS的最优/近最优车载云配置；考虑到这些问题的复杂性，我们将采用启发式/元启发式方法来解决所得到的模型。此外，我们将开发新的管理技术，以实现有效的带宽利用，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.