论文标题

在车辆云体系结构中优化的分布式处理

Optimized Distributed Processing in a Vehicular Cloud Architecture

论文作者

Behbehani, Fatemah S., Musa, Mohamed, Elgorashi, Taisir, Elmirghani, J. M. H.

论文摘要

云数据中心的引入为存储和处理数据开辟了新的可能性,从而增强了外围设备的有限功能。大型数据中心往往远离最终用户,从而增加互连网络中的延迟和功耗。这些限制导致引入边缘处理,其中小型分布式数据中心或雾单元位于网络边缘附近的最终用户的边缘。车辆可以在其板载功能(OBUS)中具有大量的处理能力,通常是未使用的。这些可用于增强网络边缘处理功能。在本文中,我们扩展了以前的工作,并开发了混合整数线性编程(MILP)公式,以优化网络和处理资源的分配以最大程度地减少功耗。我们的边缘处理体系结构包括车辆处理节点,边缘处理和云基础架构。此外,在本文中,我们的优化公式包括延迟。与功率最小化相比,我们的新配方大大减少了延迟,同时导致功耗的增加非常有限。

The introduction of cloud data centres has opened new possibilities for the storage and processing of data, augmenting the limited capabilities of peripheral devices. Large data centres tend to be located away from the end users which increases latency and power consumption in the interconnecting networks. These limitations led to the introduction of edge processing where small distributed data centres or fog units are located at the edge of the network close to the end user. Vehicles can have substantial processing capabilities, often un-used, in their on-board-units (OBUs). These can be used to augment the network edge processing capabilities. In this paper we extend our previous work and develop a mixed integer linear programming (MILP) formulation that optimizes the allocation of networking and processing resources to minimize power consumption. Our edge processing architecture includes vehicular processing nodes, edge processing and cloud infrastructure. Furthermore, in this paper our optimization formulation includes delay. Compared to power minimization, our new formulation reduces delay significantly, while resulting in a very limited increase in power consumption.

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