Syed Sidra Abid, Rashid Munaf, Hussain Samreen, Azim Fahad, Zahid Hira, Umer Asif, Waheed Abdul, Zareei Mahdi, Vargas-Rosales Cesar
Department of Biomedical Engineering, Faculty of ESTM, Ziauddin University, Karachi 74600, Pakistan.
Department of Electrical and Software Engineering, Faculty of ESTM, Ziauddin University, Karachi 74600, Pakistan.
Sensors (Basel). 2022 Jan 5;22(1):401. doi: 10.3390/s22010401.
Software-defined network (SDN) and vehicular ad-hoc network (VANET) combined provided a software-defined vehicular network (SDVN). To increase the quality of service (QoS) of vehicle communication and to make the overall process efficient, researchers are working on VANET communication systems. Current research work has made many strides, but due to the following limitations, it needs further investigation and research: Cloud computing is used for messages/tasks execution instead of fog computing, which increases response time. Furthermore, a fault tolerance mechanism is used to reduce the tasks/messages failure ratio. We proposed QoS aware and fault tolerance-based software-defined V vehicular networks using Cloud-fog computing (QAFT-SDVN) to address the above issues. We provided heuristic algorithms to solve the above limitations. The proposed model gets vehicle messages through SDN nodes which are placed on fog nodes. SDN controllers receive messages from nearby SDN units and prioritize the messages in two different ways. One is the message nature way, while the other one is deadline and size way of messages prioritization. SDN controller categorized in safety and non-safety messages and forward to the destination. After sending messages to their destination, we check their acknowledgment; if the destination receives the messages, then no action is taken; otherwise, we use a fault tolerance mechanism. We send the messages again. The proposed model is implemented in CloudSIm and iFogSim, and compared with the latest models. The results show that our proposed model decreased response time by 50% of the safety and non-safety messages by using fog nodes for the SDN controller. Furthermore, we reduced the execution time of the safety and non-safety messages by up to 4%. Similarly, compared with the latest model, we reduced the task failure ratio by 20%, 15%, 23.3%, and 22.5%.
软件定义网络（SDN）与车载自组织网络（VANET）相结合，形成了软件定义车载网络（SDVN）。为了提高车辆通信的服务质量（QoS）并使整个过程高效运行，研究人员正在致力于VANET通信系统的研究。当前的研究工作已经取得了很大进展，但由于以下限制，仍需要进一步的调查和研究：使用云计算来执行消息/任务，而不是雾计算，这增加了响应时间。此外，使用了容错机制来降低任务/消息的故障率。我们提出了基于云-雾计算的QoS感知和容错的软件定义V车载网络（QAFT-SDVN）来解决上述问题。我们提供了启发式算法来解决上述限制。所提出的模型通过放置在雾节点上的SDN节点获取车辆消息。SDN控制器从附近的SDN单元接收消息，并以两种不同的方式对消息进行优先级排序。一种是消息性质方式，另一种是消息优先级排序的截止日期和大小方式。SDN控制器将消息分类为安全消息和非安全消息，并转发到目的地。在将消息发送到目的地后，我们检查它们的确认情况；如果目的地接收到消息，则不采取任何行动；否则，我们使用容错机制。我们再次发送消息。所提出的模型在CloudSIm和iFogSim中实现，并与最新模型进行了比较。结果表明，我们提出的模型通过为SDN控制器使用雾节点，将安全消息和非安全消息的响应时间减少了50%。此外，我们将安全消息和非安全消息的执行时间最多减少了4%。同样，与最新模型相比，我们将任务故障率降低了20%、15%、23.3%和22.5%。
