Stabilized Clustering Enabled V2V Communication in an NDN-SDVN Environment for Content Retrieval
Stabilized Clustering Enabled V2V Communication in an NDN-SDVN Environment for Content Retrieval
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DOI：
10.1109/access.2020.3010881
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发表时间：
2020-07
期刊：
影响因子：
3.9
通讯作者：
Mazen Alowish;Yoshiaki Shiraishi;Yasuhiro Takano;M. Mohri;M. Morii
中科院分区：
文献类型：
--
作者：
Mazen Alowish;Yoshiaki Shiraishi;Yasuhiro Takano;M. Mohri;M. Morii
内容检索正在成为软件定义网络和车载自组织网络（SDVN）集成网络结构上的一种新兴应用。预计SDVN可以灵活地提供高效的分组路由，而无需部署道路侧单元。然而，在这种缺乏基础设施的环境中，从道路上车辆聚集的动态网络中检索内容是一项挑战。为了解决这一问题，我们提出了一种将命名数据网络（NDN）与SDVN （NDN-SDVN）相结合的新网络设计。新的NDN-SDVN旨在提高集群形成的稳定性，从而能够在车对车（V2V）通信中有效地执行内容检索。请注意，V2V中最重要的问题之一是如何选择集群头。提出的NDN-SDN在最大服务质量（QoS）准则下，利用SDN控制器自适应确定簇头，同时保留一个基于蛾焰优化（MFO）算法的辅助簇头，以便根据后退时间立即重组新簇。此外，NDN-SDVN中的内容检索可以在集群内和集群间通信中执行。为此，采用神经网络卡尔曼滤波（KF-NN）在一跳内选择一定数量的优选车辆，以缓解NDN中经常出现的广播风暴问题。内容检索是通过发送包含时间戳和目标MAC地址的两个附加字段的兴趣包来启动的。SDN控制器的头车对其他车兑现的内容信息保持本体，显著提高了数据包的传送率。该NDN-SDVN设计是在omnet++模拟器上开发的，并从头寿命、簇寿命、满意率、延迟和包投递率等方面对其优势效果进行了评价。
Content retrieval is becoming an emerging application on an integrated network structure referred to as Software Defined Network and Vehicular Ad hoc Network (SDVN). The SDVN is expected to flexibly provide efficient packet routing without deploying road side units. In such the infrastructure-less environment, however, it is challenging to retrieve contents from dynamic networks clustered with vehicles on roadways. As a solution to the problem, we propose a new network design by conjoining Named Data Network (NDN) with SDVN (NDN-SDVN). The new NDN-SDVN is designed as to improve stableness of the cluster formation and hence enables to efficiently perform the content retrieval over Vehicle-to-Vehicle (V2V) communications. Note that one of the most important problems in the V2V is how to select a cluster head. The proposed NDN-SDN adaptively determines the cluster head by using the SDN controller under the maximum Quality of Service (QoS) criterion, while reserving an assistance head based on a Moth Flame Optimization (MFO) algorithm to immediately recompose a new cluster with the back-off time. Moreover, the content retrieval in the NDN-SDVN can be performed over both intra- and inter-cluster communications. To this end, a Kalman filter with Neural Network (KF-NN) is applied for selecting a certain number of preferable vehicles in 1-hop in order to mitigate the broadcast storm problem that often occurs in an NDN. Content retrieval is initiated by sending interest packets including two additional fields of the timestamp and the target MAC address. The head vehicle of the SDN controller maintains ontology regarding the content information cashed by other vehicles, which significantly improves the packet delivery ratio. This NDN-SDVN design is developed on the OMNeT++ simulator and their advantageous results are evaluated in terms of the head lifetime, the cluster lifetime, the satisfactory rate, the latency and the packet delivery ratio.