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首页> 外文期刊>Communications, China >Proactive load balancing mechanism for fog computing supported by parked vehicles in IoV-SDN
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Proactive load balancing mechanism for fog computing supported by parked vehicles in IoV-SDN

机译：IOV-SDN中停放车辆支持的雾计算主动负载平衡机制

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Internet of Vehicles (IoV) is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles' sensors through the internet. These sensors generate different tasks that should be analyzed and processed in some given period of time. They send the tasks to the cloud servers but these sending operations increase bandwidth consumption and latency. Fog computing is a simple cloud at the network edge that is used to process the jobs in a short period of time instead of sending them to cloud computing facilities. In some situations, fog computing cannot execute some tasks due to lack of resources. Thus, in these situations it transfers them to cloud computing that leads to an increase in latency and bandwidth occupation again. Moreover, several fog servers may be fuelled while other servers are empty. This implies an unfair distribution of jobs. In this research study, we shall merge the software defined network (SDN) with IoV and fog computing and use the parked vehicle as assistant fog computing node. This can improve the capabilities of the fog computing layer and help in decreasing the number of migrated tasks to the cloud servers. This increases the ratio of time sensitive tasks that meet the deadline. In addition, a new load balancing strategy is proposed. It works proactively to balance the load locally and globally by the local fog managers and SDN controller, respectively. The simulation experiments show that the proposed system is more efficient than VANET-Fog-Cloud and IoV-Fog Cloud frameworks in terms of average response time and percentage of bandwidth consumption, meeting the deadline, and resource utilization.
机译：车辆互联网（IOV）是一种新型的车辆ad hoc网络，用于通过互联网将每个车辆的传感器与其他车辆传感器连接。这些传感器产生不同的任务，在某个给定的时间段内应该分析和处理。它们将任务发送到云服务器，但这些发送操作会增加带宽消耗和延迟。雾计算是网络边缘的简单云，用于在短时间内处理作业，而不是将它们发送到云计算设施。在某些情况下，由于缺乏资源，FOG计算无法执行一些任务。因此，在这些情况下，它将它们传送到云计算，以便再次导致延迟和带宽占用的增加。此外，可以加油几个雾服务器，而其他服务器是空的。这意味着没有公平的就业机会分配。在本研究中，我们将使用IOV和FOG计算合并软件定义的网络（SDN），并使用停放的车辆作为助理雾计算节点。这可以提高雾计算层的功能，并有助于将迁移任务的数量减少到云服务器。这增加了满足截止日期的时间敏感任务的比率。此外，提出了一种新的负载平衡策略。它积极地运行，分别由本地雾化管理器和SDN控制器在本地和全球范围内平衡负荷。仿真实验表明，在平均响应时间和带宽消耗的百分比，符合截止日期和资源利用率方面，所提出的系统比Vanet-Fog-Cloud和IoV-Fog云框架更有效。

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