Color Filtering Localization for Three-Dimensional Underwater Acoustic Sensor Networks

Accurate localization for mobile nodes has been an important and fundamental problem in underwater acoustic sensor networks (UASNs). The detection information returned from a mobile node is meaningful only if its location is known. In this paper, we propose two localization algorithms based on color filtering technology called PCFL and ACFL. PCFL and ACFL aim at collaboratively accomplishing accurate localization of underwater mobile nodes with minimum energy expenditure. They both adopt the overlapping signal region of task anchors which can communicate with the mobile node directly as the current sampling area. PCFL employs the projected distances between each of the task projections and the mobile node, while ACFL adopts the direct distance between each of the task anchors and the mobile node. Also the proportion factor of distance is proposed to weight the RGB values. By comparing the nearness degrees of the RGB sequences between the samples and the mobile node, samples can be filtered out. And the normalized nearness degrees are considered as the weighted standards to calculate coordinates of the mobile nodes. The simulation results show that the proposed methods have excellent localization performance and can timely localize the mobile node. The average localization error of PCFL can decline by about 30.4% than the AFLA method.Comment: 18 pages, 11 figures, 2 table

A survey of localization in wireless sensor network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

Node Localization based on Anchor Placement using Fuzzy C-Means in a Wireless Sensor Network

Localization is one of the oldest mathematical and technical problems that have been at the forefront of research and development for decades. In a wireless sensor network (WSN), nodes are not able to recognize their position. To solve this problem, studies have been done on algorithms to achieve accurate estimation of nodes in WSNs. In this paper, we present an improvement of a localization algorithm namely Gaussian mixture semi-definite programming (GM-SDP-2). GMSDP is based on the received signal strength (RSS) to achieve a maximum likelihood location estimator. The improvement lies in the placement of anchors through the Fuzzy C-Means clustering method where the cluster centers represent the anchors' positions. The simulation of the algorithm is done in Matlab and is based on two evaluation metrics, namely normalized root-mean-squared error (RMSE) and cumulative distribution function (CDF). Simulation results show that our improved algorithm achieves better performance compared to those usinga predetermined placement of anchors

Enhanced DV-Hop Algorithm for Energy Efficiency and Network Quality in Wireless Sensor Networks

Wireless Sensor Networks (WSN) are wireless networks with many sensor nodes covering a relatively large area. One of the weaknesses of WSN is the use of relatively high energy consumption, which affects the quality of network services. Although the WSN network routing using the DV-Hop algorithm is widely used because of its simplicity, improvements need to be made to improve energy efficiency so that the network lifetime is more optimal. This article proposes an enhanced DV-Hop algorithm compared to other algorithms to improve network energy efficiency and quality of service. There are three approaches to improving the DV-Hop algorithm. First, the selection of the CH node is based on the distance to the Base Station so that the selected CH node does not have a long distance from the base station. Second, the selection of CH nodes must have a number of neighbouring nodes above the average of other sensor nodes. Finally, each selected CH node calculates the minimum distance to the previously selected CH node to ensure that the selected CH nodes are not adjacent to each other. The proposed approach obtains better total data packets sent to the base station, energy efficiency, and network age using Matlab simulation software by comparing the enhanced DV-Hop algorithm with the original DV-Hop algorithm and three other routing algorithms

Localization by decreasing the impact of obstacles in wireless sensor networks

In sensor networks ,Localization techniques makes use of small number of reference nodes, whose locations are known in prior, and other nodes estimate their coordinate position from the messages they receive from the anchor nodes. Localization protocol can be divided into two categories: (i) range-based and (ii) range-free protocols. Range-based protocols depend on knowing the distance between the nodes. Where as, range-free protocols consider the contents of message sent from the anchor node to all other sensor node. Previous range-free based localization methods requires at least three anchor nodes ,whose positions already known ,in order to find the position of unknown sensor node and these methods might not guarantee for complete solution and an infeasible case could occur. The convex position estimation method takes the advantage of solving the above problem. Here different approach to solve the localization problem is described. In which it considers a single moving anchor node and each node will have a set of mobile anchor node co-ordinates. Later this algorithm checks for the connectivity between the nodes to formulate the radical constraints and finds the unknown sensor node location. The nodes position obtained using convex position estimation method will have less location error. However, Network with obstacles is most common. Localizing these networks, some nodes may have higher location error. The new method is described to decrease the impact of obstacle, in which nodes near or within the obstacle that fail to get minimum of three anchor node position values get the anchor position set from its neighbor nodes, applies the convex position estimation method and gets localized with better position accuracy. The Convex position estimation method is range-free that solves localization problem when infeasible case occurs and results in better location accuracy

A hybrid localization approach in 3D wireless sensor network

Location information acquisition is crucial for many wireless sensor network (WSN) applications. While existing localization approaches mainly focus on 2D plane, the emerging 3D localization brings WSNs closer to reality with much enhanced accuracy. Two types of 3D localization algorithms are mainly used in localization application: the range-based localization and the range-free localization. The range-based localization algorithm has strict requirements on hardware and therefore is costly to implement in practice. The range-free localization algorithm reduces the hardware cost but at the expense of low localization accuracy. On addressing the shortage of both algorithms, in this paper, we develop a novel hybrid localization scheme, which utilizes the range-based attribute RSSI and the range-free attribute hopsize, to achieve accurate yet low-cost 3D localization. As anchor node deployment strategy plays an important role in improving the localization accuracy, an anchor node configuration scheme is also developed in this work by utilizing the MIS (maximal independent set) of a network. With proper anchor node configuration and propagation model selection, using simulations, we show that our proposed algorithm improves the localization accuracy by 38.9% compared with 3D DV-HOP and 52.7% compared with 3D centroid

Selected RSSI-based DV-Hop Localization for Wireless Sensor Networks

With the increasing demand on wireless sensor networks (WSNs) applications, acquiring the information of sensor node locations becomes one of the most important issues. Up to now, available localization approaches can be categorized into range-free and range-based methods. Range-free localizations are being pursued as a more cost-effective method. However, range-based schemes have better localization accuracy. This paper proposes the selected RSSI-based DV-Hop localization, which improves localization accuracy from the existing schemes by applying a combined technique that inherits the benefits from both methods. Our proposed technique firstly employs the DV-Hop approach of range-free algorithms, then uses the received signal strength indicator (RSSI) estimation technique of range-based algorithms to estimate the distances of selected hops. This paper also includes basic studies, which have been performed via computer simulations as well as testbed experiments, for distance calculation from RSSI measurement and location estimation in order to prove the credibility of our simulator. The proposed technique is implemented and tested via our developed WSN simulation model. Results in terms of distance error in comparison with traditional DV-Hop, RDV-Hop, and weighted RSSI algorithms show significant performance improvement by using our proposed method for both low-density and high-density wireless sensor network test scenarios