Energy Constraints of Localization Techniques in Wireless Sensor Networks (WSN): A Survey <s> Range Free Technique <s> Localization algorithm continues to be an important and challenging topic in today's wireless sensor networks (WSNs). In this paper, a novel range-free localization algorithm using expected hop progress (LAEP) to predict the location of any sensor in a WSN is proposed. This algorithm is based on an accurate analysis of hop progress in a WSN with randomly deployed sensors and arbitrary node density. By deriving the expected hop progress from a network model for WSNs in terms of network parameters, the distance between any pair of sensors can be accurately computed. Since the distance estimation is a key issue in localization systems for WSNs, the proposed range-free LAEP achieves better performance and less communication overhead as compared to some existent schemes like DV-Hop and RAW. In addition, we study the effect of anchor placement on the algorithm performance by deriving the corresponding mean position error range. Extensive simulations are performed and the results are observed to be in good agreement with the theoretical analysis. <s> BIB001 </s> Energy Constraints of Localization Techniques in Wireless Sensor Networks (WSN): A Survey <s> Range Free Technique <s> Wireless sensor networks have been considered as a promising tool for many location-dependent applications. In such deployments, the requirement of low system cost prohibits many range-based methods for sensor node localization; on the other hand, range-free approaches depending only on radio connectivity may underutilize the proximity information embedded in neighborhood sensing. In response to these limitations, this paper introduces a proximity metric called RSD to capture the distance relationships among 1-hop neighboring nodes in a range-free manner. With little overhead, RSD can be conveniently applied as a transparent supporting layer for state-of-the-art connectivity-based localization solutions to achieve better accuracy. We implemented RSD with three well-known algorithms and evaluated using two outdoor test beds: an 850-foot-long linear network with 54 MICAz motes, and a regular 2D network covering an area of 10,000 square feet with 49 motes. Results show that our design helps eliminate estimation ambiguity with a subhop resolution, and reduces localization errors by as much as 35 percent. In addition, simulations confirm its effectiveness for large-scale networks and reveal an interesting feature of robustness under unevenly distributed radio path loss. <s> BIB002 </s> Energy Constraints of Localization Techniques in Wireless Sensor Networks (WSN): A Survey <s> Range Free Technique <s> Node localization is a main application of wireless sensor networks. However, the measurement error and noise in a real environment make the positioning of information nonlinear and have a great effect on the performance of localization methods. In this paper, we propose a novel isometric mapping (Isomap) node localization algorithm based on partial least squares (PLS-Isomap). For topological stability, the critical outlier points are eliminated by comparing the contribution rate of all data points. Then, we employ the PLS method to solve the Isomap. The adoption of PLS reduces the noise sensitivity of Isomap, which achieves solution by least squares. Moreover, the proposed approach applies a projection method to construct a new kernel matrix between new and original data points. Compared with Isomap and the multidimensional scale method, experimental and simulation results indicate that the PLS-Isomap algorithm has good topological stability, robustness, positioning accuracy, and lower computational complexity. <s> BIB003
Range-free approaches for localization are based on sensor nodes wireless connectivity and topology to estimate the location of unknown sensor nodes BIB002 BIB001 . These techniques provide advantages of low cost, small communication traffic, no extra hardware and provide some degree of precision to localization, sometimes even better than some range based methods. However, a large number of static anchor nodes (nodes with known coordinates) and specific deployment is required for a high degree of accuracy, thereby increasing the cost of implementing this method BIB003 .