DV-Hop localization methods for displaced sensor nodes in wireless sensor network using PSO

Kanwar, Vivek; Kumar, Ashok

doi:10.1007/s11276-020-02446-5

Cited by 43 publications

(25 citation statements)

References 23 publications

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“…The simulation results had shown that adaptive Fp algorithm was superior to other algorithms in terms of convergence speed and localization error. The PSO algorithm was used for DV-Hop localization of displaced sensor nodes in [ 75 ], and radio irregularity model was considered for simulation. The elapsed time, localization error and energy consumption of PSO algorithm were less than those of the existing algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics

2022

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Wireless sensor networks (WSNs) contain sensor nodes in enormous amount to accumulate the information about the nearby surroundings, and this information is insignificant until the exact position from where data have been collected is revealed. Localization of sensor nodes in WSNs plays a significant role in several applications such as detecting the enemy movement in military applications. The major aim of localization problem is to find the coordinates of all target nodes with the help of anchor nodes. In this paper, two variants of bat optimization algorithm (BOA) are proposed to localize the sensor nodes in a more efficient way and to overcome the drawbacks of original BOA, i.e. being trapped in local optimum solution. The exploration and exploitation features of original BOA are modified in the proposed BOA variants 1 and 2 using improved global and local search strategies. To validate the efficiency of the proposed BOA variants 1 and 2, several simulations have been performed for various numbers of target nodes and anchor nodes, and the results are compared with original BOA and other existing optimization algorithms applied to node localization problem. The proposed BOA variants 1 and 2 outperform the other algorithms in terms of mean localization error, number of localized nodes and computing time. Further, the proposed BOA variants 1 and 2 and original BOA are also compared in terms of various errors and localization efficiency for several values of target and anchor nodes. The simulations results signify that the proposed BOA variant 2 is superior to the proposed BOA variant 1 and existing BOA in terms of several errors. The node localization based on the proposed BOA variant 2 is more effective as it takes less time to perform computations and has less mean localization error than the proposed BOA variant 1, BOA and other existing optimization algorithms.

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Section: Literature Reviewmentioning

confidence: 99%

Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics

2022

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“…Finally, a professional and stable team of volunteers should be formed, and through systematic training, the volunteer service team should provide comprehensive and three-dimensional service and logistical support for the event. Even if we are well prepared, there will still be more or less unexpected events, big or small, in the preparation or event holding stage, so we should do a good job of an emergency handling plan [20]. Optimization methods are a mathematical approach, which is a general term for a number of disciplines that study how to seek certain factors to optimize a given metric under a given constraint.…”

Section: Optimization Measures For Sports Event Managementmentioning

confidence: 99%

Optimization of Sports Event Management System Based on Wireless Sensor Network

et al. 2021

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In recent years, wireless sensor network technology has developed rapidly and its role in managing systems for sports events has been widely used. Wireless sensor networks not only have low wiring cost, high monitoring accuracy, and good fault tolerance but also can be monitored remotely and have outstanding advantages in fault diagnosis and safety monitoring. In this paper, firstly, the wireless sensor network hierarchical routing protocol is studied and its network model and workflow are analyzed; according to the energy consumption of the wireless sensor network, the selection method of the optimal number of cluster heads is proposed to analyze the advantages and disadvantages existing in the protocol. Secondly, the improvement of the routing protocol is proposed to address the problems of uneven distribution of cluster heads and cluster head election without considering the residual energy of nodes in the protocol. When dividing clusters, the number of neighboring nodes is considered so that cluster heads are distributed more evenly in the network; when electing cluster heads, the residual energy of nodes in the cluster is considered to balance the whole network load, and when electing cluster heads, the residual energy of nodes in the cluster is considered to balance the whole network load. Finally, simulation experiments are conducted in this paper using simulation software, and the simulation results show that the data fusion algorithm is more effective than the protocol in reducing the average energy consumption of nodes and extending the network lifetime; these features make wireless sensors more beneficial for better management of sporting events as well as better optimization.

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“…But, in scenarios such as landslides, nodes get dislocated within the network. Reference [24] reported a new DV-Hop framework with particle swarm optimization to handle the scenario of node displacement. To improve the positioning accuracy in the case of non-uniform deployment of nodes, an improved DV-Hop localization called MMSDV-Hop is reported in [25].…”

Section: Related Workmentioning

confidence: 99%

A Method for Fault Tolerant Localization of Heterogeneous Wireless Sensor Networks

Bhat

Santhosh

2021

IEEE Access

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Location information of nodes in Wireless Sensor Networks (WSN) is essential to identify the origins of events and to act on them. Several localization algorithms are developed for this purpose. In this work, we have considered hop based localization algorithms, which are popularly used in WSN applications. These algorithms use a few reference nodes with location information and localize other nodes with reference to these nodes. But, in practical scenarios, some reference nodes may turn faulty and report incorrect location information to other nodes. This reduces the localization accuracy of the entire network. Therefore, it is essential to identify and filter out faulty reference nodes from the localization process. But, in Heterogeneous Wireless Sensor Networks (HWSN), since both faulty nodes and heterogeneous nodes modify hop distances, it becomes even more challenging to identify only faulty nodes among a set of heterogeneous nodes. In this work, we have reported a fault filtering method that can be used with any of the existing hop based localization algorithms for fault-tolerant localization. This method first normalizes the distance estimations using the communication radius of nodes and then uses the Jenks Natural Breaks algorithm for filtering out the nodes producing inconsistent distance estimations. The reported method is incorporated into existing localization algorithms and tested in 2D/3D, isotropic/anisotropic environments. The results show an improvement of 14%, 52%, and 51% in localization accuracy when tested with DV-Hop, Weighted DV-Hop, and HHO-AM algorithms, respectively.

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DV-Hop localization methods for displaced sensor nodes in wireless sensor network using PSO

Cited by 43 publications

References 23 publications

Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics

Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics

Optimization of Sports Event Management System Based on Wireless Sensor Network

A Method for Fault Tolerant Localization of Heterogeneous Wireless Sensor Networks

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