A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. 3D MDS Based Localization for WSNs-IoT <s> Coverage and connectivity issues of three-dimensional (3D) networks are addressed in [2], but that work assumes that a node can be placed at any arbitrary location. In this work, we drop that assumption and rather assume that nodes are uniformly and densely deployed in a 3D space. We want to devise a mechanism that keeps some nodes active and puts other nodes into sleep so that the number of active nodes at a time is minimized (and thus network life time is maximized), while maintaining full coverage and connectivity. One simple way to do that is to partition the 3D space into cells, and only one node in each cell remains active at a time. Our results show that the number of active nodes can be minimized if the shape of each cell is a truncated octahedron. It requires the sensing range to be at least 0.542326 times the transmission radius. This value is 0.5, 0.53452 and 0.5 for cube, hexagonal prism, and rhombic dodecahedron, respectively. However, at a time the number of active nodes for cube, hexagonal prism and rhombic dodecahedron model is respectively 2.372239, 1.82615 and 1.49468 times of that of truncated octahedron model. So clearly truncated octahedron model has the highest network lifetime. We also provide a distributed topology control algorithm that can be used by each sensor node to determine its cell id using a constant number of local arithmetic operations provided that the sensor node knows its location. We also validate our results by simulation. <s> BIB001 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. 3D MDS Based Localization for WSNs-IoT <s> Node localization is very important in Wireless Sensor Network (WSN) and distance estimation between pairs of nodes is the prerequisite for localization and thus the applicability of the reported events. The paper proposes a novel distance estimation algorithm to estimate distances of each node to every other node in the network. The main contribution of the paper is the definition of a dissimilarity matrix representing the distance of each node to every other node in the network. MDS based localization algorithm is used to determine coordinates of the node in a local coordinate system and Helmert Transformation is used to convert the local coordinates of the node into a global coordinate system. The effect of various parameters affecting the performance of proposed algorithm is also presented in the paper. Finally, the efficiency of the proposed algorithm is established through the simulation results. <s> BIB002 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. 3D MDS Based Localization for WSNs-IoT <s> Node localization of wireless sensor network is a hot topic, but current algorithms of 3D wireless sensor node localization are not accurate enough. In this paper, the DR-MDS algorithm is proposed, DR-MDS algorithm mainly calibrates the coordinates of nodes and the ranging of nodes based on multidimensional scaling, it calculates the distance between any nodes exactly according to the hexahedral measurement, introducing a modification factor to calibrate the measuring distance by Received Signal Strength Indicator(RSSI). Results of simulation show that DR-MDS algorithm has significant improvement in localization accuracy compare with MDS-MAP algorithm. <s> BIB003 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. 3D MDS Based Localization for WSNs-IoT <s> With the increasing demand of smart objects in our everyday life promotes an advance generation of communications under the umbrella of the Internet of Things (IoT). For IoT, location-based service is one of the main service, while localization accuracy is a primary problem. Rather than linearizing the nonlinear cost function, we propose a novel subspace algorithm by using the time of arrival (TOA) measurements. Our propose algorithm provide closed-form solution and is validated to be robust even for large measurement noise, as the dimension awareness and eigenstructure of scalar product matrix is used. We evaluate the proposed algorithm by comparing with Cramer-Rao Lower Bound (CRLB) and show its performance through simulation experiments using MATLAB. <s> BIB004 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. 3D MDS Based Localization for WSNs-IoT <s> Nodes positioning has recently been of great interest in wireless networks owing to its crucial role in many applications. In wireless sensor networks WSNs, the task of localising sensor nodes with unknown position is important for efficient network configuration and operation. This challenge has stimulated research of various localisation algorithms. In this paper we propose robust localisation algorithm for large scale three-dimensional 3D WSNs based on multidimensional scaling MDS. Our approach has two main improvements over classical MDS algorithm. Firstly, it uses heuristic approach for distance matrix calculation, and secondly, it applies Levenberg-Marquardt LM method for absolute map refinement using received signal strength RSS measurements. Furthermore, the performance of the proposed approach is compared to other 3D WSN localisation techniques and it is shown that the proposed approach outperforms other techniques for 3D localisation. <s> BIB005 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. 3D MDS Based Localization for WSNs-IoT <s> In the recent years, there has been a huge advancement in wireless sensor computing technology. Today, wireless sensor network (WSN) has become a key technology for different types of smart environment. Nodes localization in WSN has arisen as a very challenging problem in the research community. Most of the applications for WSN are not useful without a priory known nodes positions. Adding GPS receivers to each node is an expensive solution and inapplicable for indoor environments. In this paper, we implemented and evaluated an algorithm based on multidimensional scaling (MDS) technique for three-dimensional (3D) nodes localization in WSN using improved heuristic method for distance calculation. Using extensive simulations we investigated our approach regarding various network parameters. We compared the results from the simulations with other approaches for 3D-WSN localization and showed that our approach outperforms other techniques in terms of accuracy. <s> BIB006 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. 3D MDS Based Localization for WSNs-IoT <s> The demand of smart objects in our life promotes an advanced generation of communications under the umbrella of Internet of Things (IoT). In IoT, location-based service is one of the most promising services, where localization accuracy is a crucial problem. Rather than linearizing a nonlinear cost function used in ordinary localization problem, we propose a novel subspace algorithm by using the time of arrival (TOA) measurements. Our algorithm provides a closed-form solution and is validated to be robust for large measurement noise, as the dimension awareness and eigen structure of scalar product matrix are used. Moreover, we develop a Cramer-Rao Lower Bound (CLB) for 3-dimensional (3D) localization by using the TOA measurements. We evaluate the proposed algorithm by comparing with CLB and show its performance through simulation experiments. <s> BIB007
Number of 2D MDS based localization methods for WSNsIoTs have been discussed in Section III-B to Section III-D. There are various MDS-based accurate localization algorithms proposed for 2D WSNs, but in real-world applications, 3D localization is often needed for better estimation and accuracy. Due to the 3D node deployment and complex environmental factors, the localization algorithms which are effective in 2D environments, have large localization error in the 3D case and therefore cannot be directly applied BIB001 . For example, in 2D WSNs, the location of all the nodes in the network can be computed with the help of three anchors while in 3D networks at least 4 anchors are required. Similarly, the 3D localization technique cannot be directly extended from the 2D solution by just increasing one extra dimension. There are several problems which can be solved using 2D localization but are much more complex when modeled in 3D space. For example, the distance between any two neighbor nodes in a 2D network is considered as Euclidian distance; however, in a 3D environment, the distances are geodesic rather than Euclidian. Similarly, in 2D networks, the nodes have sufficient connectivity for a given density; however, for the same density, the connectivity is low in the 3D environment due to various obstructions. Hence, localization of WSNs-IoTs in 3D space is an interesting and challenging task. In BIB005 , BIB006 BIB002 BIB003  the authors proposed 3D localization for WSNs based on MDS. In recent past the authors in BIB004 , BIB007 proposed 3D semi-centralized MDS based localization methods for IoT networks.