Study Of The Localization Algorithm For Asymmetry Distributed Wireless Sensor Network

In wireless sensor networks where many applications will normally need to locate the target or events, while the coordinates of the node's own right to provide monitoring information is the premise of the event location information, and wireless sensor networks, some of the routing mechanism and topology control, also depends on the sensor nodes in the network location information. The localization is one of the important support technologies for wireless sensor networks.Along with the wireless sensor network application scope's expansion, the sensor node's arrangement inevitable will have the asymmetry distribution condition, but the general node localization algorithm will carry on the analysis based on uniform distribution's network.First, this article main researched the Range-Free localization algorithms; Second, emphatically introduced the realized mechanism for the traditional DV-Hop algorithm, and has analyzed when it be applied in the asymmetry distributed networks, the anchor node calculates their average hop distance and the unknown nodes in calculating the distance to anchor node insufficiency;At last, above its rationale, separately used the radial direction base (RBF) neural network and the differential localization thought to revise the average hop distance and the distance between the unknown nodes and the anchor nodes, proposed two kinds of localization algorithms and they are suitable for the asymmetry distributed networks, which named: RBF-DV-Hop algorithm and D-DV-Hop algorithm; Used weighted average thought to recomputate the networks'average hop distance, and with some repeater strategy to propose the W-DV-Hop algorithm. In order to confirm the algorithms'performance, has realized the original algorithm and the improvement algorithms. Through algorithm carries on the comparison with the DV-Hop algorithm as well as Hop-count the method algorithm, the experiment proved that the improved algorithms without increased the nodes'extra disposition, and the improvement algorithms enhanced the positioning accuracy effectively under the asymmetry distribution networks.