Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch.
Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch.
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DOI：
10.3390/s16010108
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发表时间：
2016-01-19
期刊：
影响因子：
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通讯作者：
Liu J
中科院分区：
文献类型：
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作者：
Huang T;Yan S;Yang F;Pan T;Liu J
软件定义的车载传感器网络在农业中的应用，如基于无线多传感器网络的自主车辆导航，可以带来更高效的精准农业。在基于SDN的车辆传感器网络中，通过引入集中式控制器，简化了数据平面，提高了效率。然而，在无线环境中，由于动态拓扑变化或不稳定的无线信号，主控制器节点可能离开传感器网络，使得其余网络设备不受控制，例如，作为交换机的传感器节点可以根据过时规则转发分组，直到控制器更新流表条目。针对这一问题，本文提出了一种新的基于SDN的车载传感器网络体系结构，该结构可以最小化控制器连接丢失的性能损失。我们通过设计连接状态检测和自学习机制来实现这一点。我们基于扩展的Open vSwitch和Ryu构建原型。实验结果表明，控制器连接丢失的恢复时间在100ms以内，并保持规则的实时更新和稳定的吞吐量。该架构提高了精准农业中基于SDN的车载传感器网络的生存性和稳定性。
Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture.