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Abstract In the practical application of node positioning in the Internet of Things (IOT), the distribution of beacon nodes is generally non-uniform, so there is a certain error in positioning accuracy. In order to make the positioning more accurate, The MMSDV-Hop localization algorithm which improved DV-Hop localization algorithm is proposed in this paper. At first, this algorithm needs to determine the valid beacon nodes in a local range by selecting threshold value, and after using minimization criterion of mean-square error and correcting to obtain the final average hop distance. The dynamic weight is added with the hop number and the number of valid nodes as weights to determine the distance between the unknown nodes and the beacon nodes. A Weighted centroid localization algorithm and a weighted least square method are used to obtain an estimated position separately and the final position is determined by the arithmetic mean value of the two estimated positions. The Matlab simulation experiment shows that compared with the DV-Hop localization algorithm, the improved MMSDV-Hop localization algorithm has increased significantly in the positioning accuracy. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a distributed range-free node localization algorithm for three-dimensional (3D) wireless sensor networks (WSNs), named as 3D-GAIDV Hop (3D genetic algorithm based Improved Distance Vector Hop). In the proposed algorithm, the average hop size of anchor nodes is modified by updating a correction factor and the modified hop size is further optimized by line search algorithm. The concept of coplanarity is introduced to reduce location errors caused by the anchor nodes which are coplanar. The localization accuracy is further improved by applying genetic algorithm (GA). To improve the positioning coverage of the network, those target nodes which have been localized successfully in the first round of the localization process, are upgraded to assistant anchor node. All the processes and calculations are carried out at target node level, which makes the proposed algorithm energy efficient. Simulation results show that our proposed algorithm outperforms the similar kind of existing algorithms. [ABSTRACT FROM AUTHOR]

Accurate localization of underwater acoustic sensor networks is one of the essential operations. The range-free DV-Hop technique is more acceptable due to its low hardware cost and simplicity than the range-based approach. But the main drawback of this basic DV-Hop method is low accuracy and link failure due to maintenance or short battery life during the continuous localization calculation in the underwater scenario. Most algorithms in this field do not pay enough attention to the mobility of the nodes. By examining the movement patterns of water, this manuscript uses a technique for UWSN localization based on a mobility prediction algorithm. This manuscript proposed a reference node-based multi-hop improved DV-Hop​ technique using School Topper Optimization (STO) and mobility prediction algorithms. This proposed scheme's highlighted advantage is to reduce the localization error to identify the unknown target nodes using a reference node-based localization scheme using a mobility prediction algorithm without increasing the beacon nodes, and the multi-hop improved DV-Hop​ algorithm using STO significantly improved the link failure problem by iteratively selecting the different sets of the beacon nodes in the same scenario The simulation report has proved that our framework takes better computational time, has a better convergence rate by introducing the STO technique, provides 23.76% and 37.18% better avg. localization error and localization error variance, and 16.12% better coverage from PSODV-Hop and GSODV-Hop techniques. [ABSTRACT FROM AUTHOR]

Abstract: Wireless Sensor Networks, which can real-time monitor and acquire information in the distribution area of network, have a widely application in the next generation network. Localization of nodes is a key technology for application of wireless sensor networks, and it has attracted significant interest in recent years. According to the localization principle of the DV-Hop algorithm, we propose an improved localization algorithm that has three improvements including the estimation of average single hop distance, the calculation of distance between unknown nodes and anchor nodes and the estimation of node positions. These improvements can be used to replace the corresponding steps in the DV-Hop algorithm, and localization performances are analyzed in theory and in simulations. The results show that the proposed improvements can greatly enhance the localization accuracy of the unknown nodes. In addition, the proposed schemes do not change the localization process of the DV-Hop algorithm, and hence they need no further communication resource and additional hardware requirement. [Copyright &y& Elsevier]

• A smart safety early warning system based on improved DV-Hop localization algorithm for WSNs. • Choosing anchor nodes and calculating per-hop distance are different from the original DV-Hop. • Using role-reversing weighted distance correction strategy to upgrade the positioning accuracy. • Using multi-equation selection strategy and centroid location algorithm to reduce locating error. Safety is the primary consideration of underground operation. At present, many large mineral countries are committed to using wireless sensors to reduce the accident rate and prevent casualties and major economic losses through early warning. The existing monitoring and early warning system of wired coal mine can only be used in the main tunnel, while the complex underground working area is still the "blind area" of monitoring and early warning. This paper proposes a smart safety monitoring system based on improved DV-Hop localization algorithm for randomly deployed wireless sensor networks (WSNs), which can position accurate personal tracking in industrial fields, such as mines, underground operations, tunnel engineering, and underground engineering. By choosing anchor nodes and calculating the average per-hop distance between anchor nodes are considerably different from the original DV-Hop. Based on the improved DV-Hop positioning algorithm, the critical safety data related to underground coal mining and associated with the location of the staff can be extracted precisely and analyzed quickly. The simulations show that the enhanced algorithms are able to effectively improve localization accuracy for randomly distributed sensor networks and ensure its safety in complex environment and improve the level of safety production. [ABSTRACT FROM AUTHOR]