A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> A new incremental optimization algorithm called normalized incremental subgradient (NIS) algorithm is proposed in this letter, which can be used for distributed maximum likelihood estimation (MLE). Its convergence with a diminishing stepsize has been proved and analyzed theoretically. We then apply the NIS algorithm to the energy-based sensor network source localization problem where the decay factor of the energy decay model is unknown. Simulation results show it can achieve very high estimation performance, which is only somewhat lower than that of the centralized localization method based on global optimization techniques, but with hundreds of times lower computational complexity than the centralized method. <s> BIB001 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> Nowadays, wireless sensor network (WSN) is paid more and more attention in wireless communication researches. Since location information is widely requested in various location-dependent applications, localization algorithm is becoming an important issue in WSN. As one of the range-free localization algorithms, DV-hop algorithm can be simply implemented in real WSN. In this paper, we propose a reasonable placement strategy of anchor nodes. Based on this placement strategy, a new long range localization DV-hop algorithm (PLR DV-hop), which needs no additional hardware device, is offered. Simulation results confirm that PLR DV-hop performs better than original DV-hop algorithm: it consumes less power and can provide more accurate location estimation. <s> BIB002 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <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> BIB003 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> In this article, we address the issue of localization in anisotropic sensor networks. Anisotropic networks differ from isotropic networks in that they possess properties that vary according to the direction of measurement. Anisotropic characteristics result from various factors such as the geographic shape of the region (nonconvex region), different node densities, irregular radio patterns, and anisotropic terrain conditions. In order to characterize anisotropic features, we devise a linear mapping method that projects one embedding space built upon proximity measures into geographic distance space by using the truncated singular value decomposition (SVD) pseudo-inverse technique. This transformation retains as much topological information as possible and reduces the effect of measurement noise on the estimates of geographic distances. We show via simulation that the proposed localization method outperforms DV-hop, DV-distance, and MDS-MAP, and makes robust and accurate estimates of sensor locations in both isotropic and anisotropic sensor networks. <s> BIB004 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> Mobile anchor node is used for localization in Wireless Sensor Networks. It can lower the cost of network and reduce the dependence of localization precision of the algorithm on the density of anchor nodes. However, in the existing algorithm for the localization of mobile anchor node, little research in detail has been done on the path of mobile anchor node and the timing of sending beacon. In this article, a Mobile Anchor Node Localization based on Archimedes Curve is put forth, which avoids the node's receipt of beacon on a line to the utmost extent due to the anchor node moving alone curvilinear path. In addition, the identification of the communication range of mobile anchor node and the time of sending beacon can eliminate the blind zone of beacon coverage in the network, and secure that every node can receive three beacons at least, thus achieving a relatively accurate localization for all nodes in the network. Simulation result shows lower average error of localization and better performance than DV-HOP and the localization algorithm in which anchor node moving alone scan-line. <s> BIB005 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> In this paper, we propose a novel localization algorithm in Wireless Sensor Network. The proposed method is a kind of range-free localization algorithm which only uses the proximity information between sensor nodes. In the proposed method, a robust weighted algorithm is presented to calculate the average hop distances between sensor nodes and anchor nodes. The proposed method is applied to an isotropic network and three anisotropic networks. The simulation results demonstrate that the proposed method shows excellent and robust location estimation results. <s> BIB006 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> The localization principle and error source of DV-Hop algorithm which is classic self-localization algorithm in wireless network are introduced in this paper. Aiming at the disadvantage of DV-Hop algorithm on localization accuracy, an improved scheme by modifying the average hop distance is proposed. The simulation results show that the comprehensive properties of the improved algorithm (including the localization accuracy, communication expenses, computational complexity and hardware facilities, etc) have obvious advantages compared to the basic DV-Hop algorithm. It improves node localization accuracy largely by paying little price. <s> BIB007 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> DV-Hop algorithm produces errors in location estimations due to inaccurate hop size. We propose a novel localization scheme based on DV-Hop to improve positioning accuracy with least error hop sizes of anchors and average hop sizes of unknowns. The least error hop size of an anchor minimizes its location error, but it may be far small or large. To cope with this inconsistent hop size, each unknown node calculates its average hop size with hop sizes from anchors. Simulation results show that the proposed algorithm outperforms the DV-Hop algorithm in location estimations. <s> BIB008 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> In this paper, we propose a new range-free localization algorithm called optimal proximity distance map using quadratic programming (OPDMQP). First, the relationship between geographical distances and proximity among sensor nodes in the given wireless sensor network is mathematically built. Then, the characteristics of the given network is represented as a set of constraints on the given network topology and the localization problem is formulated into a quadratic programming problem. Finally, the proposed method is applied to two anisotropic networks the topologies of which are very similar to those of the real-world applications. Unlike the most of previous localization methods which work well in the isotropic networks but not in the anisotropic networks, it is shown that the proposed method exhibits excellent and robust performances not only in the isotropic networks but also in the anisotropic networks. <s> BIB009 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <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> BIB010 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to illustrate the effectiveness of the algorithm. <s> BIB011 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> Most monitoring or tracking applications require the localization information in wireless sensor network. The DV-Hop[1] provides a basic scheme to retrieve the localization without GPS information. DV-Hop scheme only uses the localizations of the reference nodes and the hop-count, so the fundamental estimation may cause the larger error than range-based schemes. The proposed scheme uses the neighbor information to improve the accuracy in the distance estimation. A node finds the orders of its neighbors, and the orders means how close of them. The proposed analysis model reveals the probability distribution of the distance with different orders. According to the analysis model, a node retrieves the distance, called order distance, to provide the approximate location. The simulation results show our scheme outperforms than the DV-Hop in the location accuracy. For example, the average error distance is 1.09 in our scheme and 1.4 in DV-hop with the average node density 9.42. <s> BIB012 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> This paper proposes a range-free localization scheme for wireless sensor networks (WSNs) using mobile anchor nodes equipped with four directional antennas. In the proposed approach, each mobile anchor node determines its position via GPS, and then broadcasts its coordinates as it moves through the WSN. The sensor nodes detect these beacon messages and utilize a simple processing scheme to determine their own coordinates based on those of the anchors. The proposed approach removes the requirement for specific ranging hardware on the sensor nodes, avoids the need for communications between the sensor nodes. Moreover, the scheme is robust toward the effects of variations in the transmission range of the anchor nodes and the presence of obstacles in the sensing environment. The performance of the proposed scheme is evaluated by conducting a series of simulations using the ns-2 network simulator. The results show that the proposed localization scheme achieves a reduced localization error and a lower energy consumption than existing range-free solutions based on mobile anchor nodes over a wide range of typical network conditions. <s> BIB013 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> Underwater Wireless Sensor Networks (UWSNs) are expected to support a variety of civilian and military applications. Sensed data can only be interpreted meaningfully when referenced to the location of the sensor, making localization an important problem. While Global Positioning System (GPS) receivers are commonly used in terrestrial WSNs to achieve this, this is infeasible in UWSNs as GPS signals do not propagate through water. Acoustic communications is the most promising mode of communication underwater. However, underwater acoustic channels are characterized by harsh physical layer conditions with low bandwidth, high propagation delay and high bit er <s> BIB014 </s> A Survey of Localization in Wireless Sensor Network <s> Hop-Count-Based Localization. <s> The optimizing algorithm for selection of reference nodes used in mobile positioning based on trilateration in wireless ad hoc networks is proposed in the paper. Position of reference nodes plays important role from positioning accuracy point of view. In case, that there is possibility to select some reference nodes from all it is useful do it. Therefore, there will be selected reference nodes which position is optimal in respect of localized blindfolded node. The properties and function of proposed algorithm are verified by means of simulation model of wireless ad hoc network. The following positioning methods DV-Hop, DV-Distance a DV-Euclidean are implemented into simulation model, because final position estimation of these methods is based on circular trilateration. More accurate results were achieved by implementation of proposed algorithm compare with the basic algorithms. Ill. 8, bibl. 10, tabl. 2 (in English; abstracts in English, Russian and Lithuanian). <s> BIB015
As range-free positioning system, DV-Hop is the typical representation. It does not need to measure the absolute distance between the beacon node and unknown node. It uses the average hop distance to approximate the actual distances and reduces the hardware requirements. It is easy to implement and applicable to large network. But the positioning error is also correspondingly increased. The positioning process of DV-Hop is divided into three stages: information broadcast, distance calculation, and position estimation. In information broadcast stage, the beacon nodes broadcast their location information package which includes hop count and is initialized to zero for their neighbors. The receiver records the minimal hop of each beacon nodes and ignores the larger hop for the same beacon nodes. Then the receiver increases the hop count by 1 and transmits it to neighbor nodes. All the nodes in a network can record the minimal hop counts of each beacon nodes. In distance calculation stage, according to the position of the beacon node and hop count, each beacon node uses the following equation to estimate the actual distance of every hop: where (x i , y i ) and (x j , y j ) are the coordinates of beacon nodes i and j, respectively. h j is the hop count between the beacon nodes. Then, beacon nodes will calculate the average distance and broadcast the information to network. The unknown nodes only record the first average distance and then transmit it to neighbor nodes. Finally, the unknown node calculates its location through BIB001 . In order to improve the localization accuracy, the improved algorithm mainly focuses on the following several aspects: average hop distance between beacon nodes, deployment of the beacon nodes, and node information. (1) Average Hop Distance between Beacon Nodes. In the randomly deployed node density and connectivity network, Wang et al. BIB003 proposed a hop progress analytical model to estimate the optimal path distance between any pair of sensor nodes in the network. And it derived an expected hop progress and hop counts estimation method. A rangefree localization algorithm (LAEP) which is using the trilateration techniques and the expected hop progress analytical results is proposed. Unlike the DV-Hop method, the LAEP broadcasts the anchor coordinated and the corresponding estimated distance to each sensor at the same time; therefore, it can dramatically reduce the network traffic and the communication delay. Wang only considers the node's receipt of beacon on a line to the utmost extent. Xu et al. BIB005 proposed a mobile anchor node localization method that is based on Archimedes curve. It takes communication path as curve spread. It avoids the error caused by large straight line dissemination and improves the precision. Lee et al. BIB006 proposed a robust weighted algorithm which is based on DV-Hop algorithm to calculate the average hop distances between unknown nodes and anchor nodes. It applies to most topological structure networks and reduces the location error. In the same way, Zhang et al. BIB007 improved the average hop distance based on minimum mean square error standard, which reduced positioning error. Lee et al. BIB008 used Karush-Kuhn-Tucker (KKT) standards and Lagrange's mean value theorem to correct the average hop distance error and improve location accuracy. (2) Deployment of the Beacon Nodes. According to the ideal or regular node deployment scheme, the modified DV-Hop method is improved. Zheng et al. BIB002 firstly derived a beacon nodes deployment strategy that deploys a beacon node in the center of the area and other nodes are equally placed in the circle whose center is the center of the area and radius is half of the length of the area. Based on this deployment strategy, an accurate long-range DV-Hop algorithm is proposed. This method is adapted to large-scale network. Lee et al. BIB009 put forward a quadratic programming method to optimize International Journal of Distributed Sensor Networks 5 adjacent distance mapping. And it can be applied to the isotropic and anisotropic network. (3) Node Information. Some modified methods were proposed through the neighbor node information such as anchor information and relationship between node and anchor or topology structure to improve the DV-Hop method. Zhong and He BIB010 proposed a proximity metric called RSD (regulated signature distance) to capture the distance relationships among 1-hop neighboring nodes. This method can be conveniently applied as a transparent supporting layer for state-of-the-art connectivity-based localization solutions to achieve better accuracy. He et al. BIB011 proposed a spring swarm localization algorithm (SSLA) which uses the network topology information and a small amount of anchor node location information to calculate unknown nodes position. Chen et al. BIB012 used the information of neighbor node to make anchor node communication range to be gradient to improve accuracy. Lim and Hou BIB004 addressed the issue of localization in anisotropic sensor networks. And a linear mapping method is proposed to characterize anisotropic features. It projects one embedding space built upon proximity measures into geographic distance space by using the truncated singular value decomposition (SVD) pseudoinverse technique. This method is different from MDS-Map method and owns higher accuracy than MDS-Map algorithm and the other expanded MDS-Map algorithm. (4) Comprehensive Improvement Method. In addition to the above aspects, Brida et al. BIB015 used DV-Hop algorithm, DV-distance, DV-Euclidean algorithm, the constraint, and iteration condition that are to be added to select reference node. Then it used trilateration to find possible unknown node area, the estimated center of area as the final position. This algorithm could reduce the network energy consumption and improves localization accuracy. Chia-Ho BIB013 put forward a distributed, range-free localization algorithm. In this method, the mobile beacon node with directive antenna is used to supply the location information for the unknown node. Tan et al. BIB014 exploited acoustic communication to further research underwater range-free algorithm, especially proposing future prospect and development trend in view of the characteristic of underwater acoustic channel.