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Improving node positions in the presence of location errors in geographic routing protocol

机译:在地理路由协议中存在地位错误存在的节点位置

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In Wireless Sensor Networks (WSNs), a node location is usually estimated using GPS or network localization algorithms, but this estimation incurs some errors. In this work, we propose techniques to improve node locations and reduce the location errors. Location errors have an impact on location-based routing algorithms. Packets could be delayed in reaching the destination, or dropped due to exceeding the hop count. Altogether, this drains the energy resource of WSNs. Our techniques to reduce the location errors are as follows: First, a node identifies a subset of its neighboring nodes that have estimated Euclidian distances greater than the given communication range as OutLier (OL) nodes. A node can communicate with OL nodes because their unknown actual locations are within the communication range, but their estimated locations are not. We use, then, mathematical formulas to correct the OL locations to be within the communication range and thus close to their actual locations. This OL method works for a binary sensor model in which the radio signal strength cannot be measured, and the system works on the binary values Received or Not Received. If the sensor model can measure the radio signal strength, then in addition to the OL method, we can use a Received Signal Strength Indicator (RSSI) to calibrate the distance and to reposition the OL nodes. We call this approach OutLiers with Calibration (OLC). Finally, we incorporate our derived mathematical equations into our simulation. The simulation results show that OL and OLC reduce the miss probability of an actual next node, which means better location of the next node.
机译:在无线传感器网络(WSN)中,通常使用GPS或网络本地化算法估计节点位置,但此估计会引起一些错误。在这项工作中,我们提出了改进节点位置并减少位置错误的技术。位置错误对基于位置的路由算法产生影响。数据包可能会延迟到达目的地,或由于超过跳数而下降。完全,这会排出WSN的能量资源。我们的减少位置误差的技术如下:首先,节点识别其相邻节点的子集,其估计欧几里德距离大于给定通信范围作为异常值(OL)节点。节点可以与OL节点通信,因为它们的未知实际位置在通信范围内,但它们的估计位置不是。然后,我们使用的数学公式将OL位置校正到通信范围内,从而靠近其实际位置。该OL方法适用于没有测量无线电信号强度的二进制传感器模型,并且系统适用于接收或未接收的二进制值。如果传感器模型可以测量无线电信号强度,则除了OL方法之外,我们还可以使用接收的信号强度指示器(RSSI)来校准距离并重新定位OL节点。我们将这种方法称为校准(OLC)。最后,我们将我们的派生数学方程纳入了我们的模拟。仿真结果表明,OL和OLC降低了实际下一个节点的错过概率,这意味着更好的下一个节点的位置。

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