School of Defense Science, CCIT, National Defense University, Taoyuan 335009, Taiwan.
Computer Science and Information Engineering, CCIT, National Defense University, Taoyuan 335009, Taiwan.
Sensors (Basel). 2021 Jan 2;21(1):248. doi: 10.3390/s21010248.
In the current Internet of Things era, digital devices form complex interconnections. The statuses of objects of interest are monitored using sensors, and distributed wireless sensor networks are formed from numerous sensor nodes. Many Byzantine fault tolerance mechanisms in wireless sensor networks (WSNs) were proposed from Byzantine agreement which even with a few faulty nodes in a sensor network, most healthy nodes can reach a consensus, perform data transmission tasks, and maintain network operation. In this study, this mechanism was utilized together with the majority function technique; in particular, the proposed method uses original sensor signals to define a threshold to assert a binary value of one or zero, thereby performing data judgment and aggregation. This approach reduces node energy consumption and enables the nodes to quickly reach a consensus. Moreover, the operating performance of the network can be maintained even when problems such as node failure and faults occur within the fault tolerance range. Compared with existing algorithms, the proposed data aggregation mechanism exhibits a better network life cycle and can effectively extend the flexibility of network operations.
在当前的物联网时代，数字设备形成了复杂的互联。通过传感器来监测感兴趣对象的状态，并由大量传感器节点形成分布式无线传感器网络。无线传感器网络（WSN）中的许多拜占庭容错机制都是从拜占庭协议中提出的，即使在传感器网络中有少数故障节点，大多数健康节点也可以达成共识、执行数据传输任务并维持网络运行。在这项研究中，该机制与多数功能技术结合使用；特别是，所提出的方法使用原始传感器信号定义一个阈值来断言一个或零的二进制值，从而执行数据判断和聚合。这种方法减少了节点的能量消耗，并使节点能够快速达成共识。此外，即使在故障容忍范围内发生节点故障和故障等问题，网络的运行性能也能得以维持。与现有算法相比，所提出的数据聚合机制表现出更好的网络生命周期，并能有效地扩展网络操作的灵活性。
