An improved DV-Hop localization algorithm based on evolutionary algorithms

Mehrabi, Mahshid; Taheri, Hassan; Taghdiri, Pooria

doi:10.1007/s11235-016-0196-9

Cited by 35 publications

(26 citation statements)

References 22 publications

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“…It is also observed from the literature that a variant of DV-Hop has utilized the evolutionary optimization algorithm to improve the localization accuracy shown in [45,46,47]. A shuffled frog leaping algorithm (SFLA) with DV-Hop is introduced by [48], in which the modified hop-size is achieved with SFLA.…”

Section: Present State Of Research and Research Gapsmentioning

confidence: 99%

Energy Efficient Range-Free Localization Algorithm for Wireless Sensor Networks

Goyat

Kumar

et al. 2019

Sensors

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In this paper, an energy-efficient localization algorithm is proposed for precise localization in wireless sensor networks (WSNs) and the process is accomplished in three steps. Firstly, the beacon nodes discover their one-hop neighbor nodes with additional tone requests and reply packets over the media access control (MAC) layer to avoid collision of packets. Secondly, the discovered one-hop unknown nodes are divided into two sets, i.e. unknown nodes with direct communication, and with indirect communication for energy efficiency. In direct communication, source beacon nodes forward the information directly to the unknown nodes, but a common beacon node is selected for communication which reduces overall energy consumption during transmission in indirect communication. Finally, a correction factor is also introduced, and localized unknown nodes are upgraded into helper nodes for reducing the localization error. To analyze the efficiency and effectiveness of the proposed algorithm, various simulations are conducted and compared with the existing algorithms.

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Section: Present State Of Research and Research Gapsmentioning

confidence: 99%

Energy Efficient Range-Free Localization Algorithm for Wireless Sensor Networks

Goyat

Kumar

et al. 2019

Sensors

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“…Further, it restricts the population in the certain range so that it can prevent the energy consumption caused by insignificant search. In like manner, Mehrabi [33] combines genetic algorithm, leapfrog algorithm, and PSO algorithm and has successfully applied them into different stages of DV Hop; the leapfrog algorithm is used to get more accurate AHD, and the hybrid genetic-PSO algorithm is employed to solve the problem of greater error of multilateral localization.…”

Section: Related Workmentioning

confidence: 99%

A Connectivity Weighting DV_Hop Localization Algorithm Using Modified Artificial Bee Colony Optimization

Chen

Sun

2019

Journal of Sensors

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Node localization is a fundamental issue in wireless sensor network (WSN), as many applications depend on the precise location of the sensor nodes (SNs). Among all localization algorithms, DV_Hop is a typical range-free localization algorithm characterized by such advantages as simple realization and low energy cost. From detailed analysis of localization error for the basic DV_Hop algorithm, we propose a connectivity weighting DV_Hop localization algorithm using modified artificial bee colony optimization. Firstly, the proposed algorithm calculates the average hop distance (AHD) of anchor nodes in terms of the minimum mean squared distance error between the estimated distances of anchor nodes and the corresponding actual distances from them. After that, a connectivity weighting method, considering the influence from both local network properties of anchor nodes and the distances from anchor nodes to unknown nodes, is designed to obtain the AHD of unknown nodes. In addition, we set up the weighting calculation proportion of anchor nodes at the same time. Finally, a modified artificial bee colony algorithm which enlarges searching space is used to optimize the execution of multilateral localization. The experimental results demonstrate that the connectivity weighting approach has better localization effect, and the AHD of unknown nodes close to true value can be obtained at a relatively large probability. Moreover, the modified artificial bee colony algorithm can reduce the probability of premature convergence, and thus the localization accuracy is further improved.

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“…The DV-hop algorithm is not much complicated to implement and the problem associated with it is the improvement to localization accuracy, it can localize target nodes which have no neighbor or few neighbors anchor nodes but with less precision. For that reason, many of enhanced versions of the algorithm has been proposed in the literature [7,8,9,[10][11][12][13][14][15][16][17]. Mehrabi et.al implemented an extended version of the DV-Hop algorithm on the basis of SFLA combining GA-PSO.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Prevention Mechanism for Replay Attack in Distance Vector - HOP Localization Scheme

2019

IJITEE

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Securing the process of node localization in Wireless Sensor Network (WSN) is an important area of research. In this paper, we focus on securing Distance Vector (DV)-Hop localization scheme from Replay Attack. The DV-Hop localization algorithm is a limit free hop based reference Wireless Sensor Network architecture. It faces a couple of issues like a route discovery mechanism and threat prevention issues. This paper focuses on the establishment of a prevention mechanism for DV-Hop scheme against a Replay attack. The proposed architecture uses an Artificial Bee Colony (ABC) and Neural Network in order to prevent the attack. To prove the efficacy of the proposed scheme, the network scenario without replay attack, with replay attack and with attack after prevention mechanism is considered. The simulations are conducted for 200 iterations using MATLAB. The evaluation is done on the basis of parameters like localization error and transmission loss. Localization error of the proposed framework is similar to localization error without an attack which is about 0.57, and the maximum localized error is about 0.92. The maximum transmission loss without attack and after prevention is very close and varies by only 2 %, which is very good. The experimental results reveal that the proposed technique successfully prevents replay attack in WSN

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An improved DV-Hop localization algorithm based on evolutionary algorithms

Cited by 35 publications

References 22 publications

Energy Efficient Range-Free Localization Algorithm for Wireless Sensor Networks

Energy Efficient Range-Free Localization Algorithm for Wireless Sensor Networks

A Connectivity Weighting DV_Hop Localization Algorithm Using Modified Artificial Bee Colony Optimization

A Novel Prevention Mechanism for Replay Attack in Distance Vector - HOP Localization Scheme

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