###### Abstract  
Locating deployed sensor nodes in wireless sensor networks is a crucial issue for general environmental monitoring applications. Most current positioning technologies use stationary anchors to compute the positions of sensor nodes. However, placing the static anchors in the monitoring area is not a trivial job, especially in hazardous environments. Applying a mobile anchor is a good solution. This paper proposes an iterative sensor positioning (ISP) algorithm that uses the neighboring-positioned nodes to assist the mobile anchor in locating the unknown nodes. In addition, a mobile anchor route scheduling method, named MARS, is also proposed to shorten the traveling distance of the mobile anchor. MARS uses a projection mechanism and the ISP algorithm to reduce the traveling distance. Simulation results indicate that MARS can reduce the traveling distance of the mobile anchor by about 21-49% compared with the SCAN method. In the unfavorable scenario of the projection mechanism, MARS still provides the mobile anchor with a traveling distance that is 34% less than the SCAN method. The mobile anchor, when applying the MARS method, is able to locate all unknown nodes in only 45% to 70% of the traveling distance required by the one using the SCAN method in the scenario favorable to the ISP algorithm, while still reducing the traveling distance by 15% to 21% in the scenario unfavorable to the ISP algorithm. In the non-ideal signal scenario, the positioning size of the positioning area of the ISP algorithm when using the MARS method is about 53% to 74% less than when using the Triangulation algorithm. iterative sensor positioning; mobile anchor positioning; mobile anchor route schedule; wireless sensor networks +
Footnote †: journal: Medical  
the number of reference points therefore also implies increased costs when building the reference points. Therefore, some studies have used a mobile anchor traveling randomly within the deployment area to locate the unknown sensor nodes [25]. Due to the fact that the sensors can appear anywhere, the mobile anchor needs to be able to guarantee that its radio signal on its traveling route is able to cover all locations in the deployment area. The most typical traveling route is the straight-line mode, which scans the deployment area in order to obtain three non-collinear positions in order to locate the sensor [26; 27; 28]. A localization algorithm with a mobile anchor node based on trilateration (LMAT) [29] is proposed to solve the problem of collinear points. LMAT uses a mobile anchor moving in the scan mode with a trilateration trajectory in the deployment area. The mobile anchor periodically broadcasts its current position in order to locate the unknown nodes. A similar method combines the LMAT and SCAN algorithms, referred to as SLMAT [30], to achieve a compromise between positioning accuracy and energy consumption. Another scanning method that can be used to decrease the length of the movement path of the mobile anchor is SCAN-ET [31]. SCAN-ET firstly divides the deployment area into several smaller zones. The mobile anchor then uses the SCAN method to determine its travel path in each of the zones. If any of the smaller zones contains unknown nodes, the mobile anchor will move along the sides of the triangle in this zone, broadcasting messages at each of the vertices of the triangle. Methods similar to the SCAN methods, but with variations in the movement path, include the H-curve [32], M-curves [33], NHexCurves [34], and Z-curve [35] methods. The movement path of the mobile anchor is designed to follow a curved path [36; 37] in order to solve the problem of the collinearity of the three points. The curved path has a minimal number of straight-line segments, resulting in much less collinearity occurring during localization, as, for example, when using the CIRCLES movement trajectory, the S-CURVES movement trajectory, or the spiral trajectory. The above methods depend heavily on the mobile anchor to locate the unknown nodes.