Localization is one of the most important factor in wireless sensor networks as many applications demand position information of sensors. Recently there is an increasing interest on the use of mobile anchors for localizing sensors. Most of the works available in the literature either looks into the aspect of reducing path length of mobile anchor or tries to increase localization accuracy. The challenge is to design a movement strategy for a mobile anchor that reduces path length while meeting the requirements of a good range-free localization technique. In this paper we propose two cost-effective movement strategies i.e., path planning for a mobile anchor so that localization can be done using the localization scheme [10]. In one strategy we use a hexagonal movement pattern for the mobile anchor to localize all sensors inside a bounded rectangular region with lesser movement compared to the existing works in literature. In other strategy we consider a connected network in an unbounded region where the mobile anchor moves in the hexagonal pattern to localize the sensors. In this approach, we guarantee localization of all sensors within r 2 error-bound where r is the communication range of the mobile anchor and sensors. Our simulation results support theoretical results along with localization accuracy.
Path planning algorithms set path for mobile anchor along which it moves in the network while localization process goes on. First we look at a brief overview of the existing range free localization schemes which provides good accuracy and can be used for localization. proposed a localization scheme in @cite_13 where the sensor's position is estimated as the intersection of perpendicular bisector of two calculated chords. However this scheme suffers from short chord length problem. @cite_17 improved over that scheme using pre-arrival and post-departure points along with the beacon points to localize a sensor. Later used beacon distance more effectively as another geometric constraint and proposed a more accurate localization scheme in @cite_7 .
@cite_13 @cite_7 @cite_17
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The localization of sensor nodes is a fundamental problem in sensor networks and can be implemented using powerful and expensive beacons. Beacons, the fewer the better, can acquire their position knowledge either from GPS devices or by virtue of being manually placed. In this paper, we propose a distributed method to localization of sensor nodes using a single moving beacon, where sensor nodes compute their position estimate based on the range-free technique. Two parameters are critical to the location accuracy of sensor nodes: the radio transmission range of the beacon and how often the beacon broadcasts its position. Theoretical analysis shows that these two parameters determine the upper bound of the estimation error when the traverse route of the beacon is a straight line. We extend the position estimate when the traverse route of the beacon is randomly chosen in a real-world situation, where the radio irregularity might cause a node to miss some crucial coordinate information from the beacon. We further point out that the movement pattern of the beacon plays a pivotal role in the localization task for sensors. To minimize estimation errors, sensor nodes can carry out a variety of algorithms in accordance with the movement of the beacon. Simulation results compare variants of the distributed method in a variety of testing environments. Real experiments show that the proposed method is feasible and can estimate the location of sensor nodes accurately, given a single moving beacon. This paper describes a distributed, linear-time algorithm for localizing sensor network nodes in the presence of range measurement noise and demonstrates the algorithm on a physical network. We introduce the probabilistic notion of robust quadrilaterals as a way to avoid flip ambiguities that otherwise corrupt localization computations. We formulate the localization problem as a two-dimensional graph realization problem: given a planar graph with approximately known edge lengths, recover the Euclidean position of each vertex up to a global rotation and translation. This formulation is applicable to the localization of sensor networks in which each node can estimate the distance to each of its neighbors, but no absolute position reference such as GPS or fixed anchor nodes is available. We implemented the algorithm on a physical sensor network and empirically assessed its accuracy and performance. Also, in simulation, we demonstrate that the algorithm scales to large networks and handles real-world deployment geometries. Finally, we show how the algorithm supports localization of mobile nodes. Localization is one of the substantial issues in wireless sensor networks. Several approaches, including range-based and range-free, have been proposed to calculate positions for randomly deployed sensor nodes. With specific hardware, the range-based schemes typically achieve high accuracy based on either node-to-node distances or angles. On the other hand, the range-free mechanisms support coarse positioning accuracy with the less expense. This paper describes a range-free localization scheme using mobile anchor points. Each anchor point equipped with the GPS moves in the sensing field and broadcasts its current position periodically. The sensor nodes obtaining the information are able to compute their locations. With the scheme, no extra hardware or data communication is needed for the sensor nodes. Moreover, obstacles in the sensing fields can be tolerated. The localization mechanism has been implemented in the network simulator ns-2. The simulation results show that our scheme performed better than other range-free mechanisms. Existing localization approaches are divided into two groups: range-based and range-free. The range-free schemes often suffer from poor accuracy and low scalability, while the range-based localization approaches heavily depend on extra hardware capabilities or rely on the absolute RSSI (received signal strength indicator) values, far from practical. In this work, we propose a mobile-assisted localization scheme called perpendicular intersection (PI), setting a dedicate tradeoff between range-free and range-based approaches. Instead of directly mapping RSSI values into physical distances, by contrasting RSSI values from the mobile beacon to a sensor node, PI utilizes the geometric relationship of perpendicular intersection to compute node positions. We have implemented the prototype of PI with 100 TelosBmotes. Through comprehensive experiments, we show that PI achieves high accuracy and low overhead, significantly outperforming the existing range-based and the mobile-assisted localization schemes.