scholarly journals Genetic Algorithms for Localization in WSN

In wireless sensor networks, localization is a way to track the exact location of sensor nodes. Occasionally node localization may not be accurate due to the absence or limitation of anchor nodes. To reduce the mean localization error, soft computing techniques such as BAT and bacterial foraging driven bat algorithm (BDBA) are utilized in literature. For better localization with reduced error, in this paper, firefly driven bat algorithm (FDBA) is proposed, which combines the heuristic of firefly and BAT algorithms. Our proposed FDBA algorithm provides better localization in terms of error of 60% and 40 % less error as compared to BAT and BDBA algorithm, respectively.

Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.


2020 ◽  
Vol 14 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Amanpreet Kaur ◽  
Padam Kumar ◽  
Govind P. Gupta

Localization problem has gained a significant attention in the field of wireless sensor networks in order to support location-based services or information such as supporting geographic routing protocols, tracking events, targets, and providing security protection techniques. A number of variants of DV-Hop-based localization algorithms have been proposed and their performance is measured in terms of localization error. In all these algorithms, while determining the location of a non-anchor node, all the anchor nodes are taken into consideration. However, if only the anchors close to the node are considered, it will be possible to reduce the localization error significantly. This paper explores the effect of the close anchors in the performance of the DV-Hop-based localization algorithms and an improvement is proposed by considering only the closest anchors. The simulation results show that considering closest anchors for estimation of the location reduces localization error significantly as compared to considering all the anchors.


2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Sana Messous ◽  
Hend Liouane

One of the main issues of wireless sensor networks is localization. Besides, it is important to track and analyze the sensed information. The technique of localization can calculate node position with the help of a set of designed nodes, denoted as anchors. The set density of these anchors may be incremented or decremented because of many reasons such as maintenance, lifetime, and breakdown. The well-known Distance Vector Hop (DV-Hop) algorithm is a suitable solution for localizing nodes having few neighbor anchors. However, existing DV-Hop-based localization methods have not considered the problem of anchor breakdown which may happen during the localization process. In order to avoid this issue, an Online Sequential DV-Hop algorithm is proposed in this paper to sequentially calculate positions of nodes and improve accuracy of node localization for multihop wireless sensor networks. The algorithm deals with the variation of the number of available anchors in the network. We note that DV-Hop algorithm is used in this article to process localization of nodes by a new optimized method for the estimation of the average distance of hops between nodes. Our proposed localization method is based on an online sequential computation. Compared with the original DV-Hop and other localization methods from the literature, simulation results prove that the proposed algorithm greatly minimizes the average of localization error of sensor nodes.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaogang Qi ◽  
Xiaoke Liu ◽  
Lifang Liu

Wireless sensor networks (WSNs) are widely used in various fields to monitor and track various targets by gathering information, such as vehicle tracking and environment and health monitoring. The information gathered by the sensor nodes becomes meaningful only if it is known where it was collected from. Considering that multilateral algorithm and MDS algorithm can locate the position of each node, we proposed a localization algorithm combining the merits of these two approaches, which is called MA-MDS, to reduce the accumulation of errors in the process of multilateral positioning algorithm and improve the nodes’ positioning accuracy in WSNs. It works in more robust fashion for noise sparse networks, even with less number of anchor nodes. In the MDS positioning phase of this algorithm, the Prussian Analysis algorithm is used to obtain more accurate coordinate transformation. Through extensive simulations and the repeatable experiments under diverse representative networks, it can be confirmed that the proposed algorithm is more accurate and more efficient than the state-of-the-art algorithms.


2014 ◽  
Vol 556-562 ◽  
pp. 3666-3669
Author(s):  
Soo Young Shin ◽  
Ifa Fatihah Mohamed Zain

In this paper, we propose a binary particle swarm optimization (BPSO) algorithm for distributed node localization in wireless sensor networks (WSNs). Each unknown node performs localization under the distance measurement from three or more neighboring anchors. The node that gets localized will be used as a reference for remaining nodes. A comparison of the performances of PSO and BPSO in terms of localization error and computation time is presented using simulations in Matlab.


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jiang Minlan ◽  
Luo Jingyuan ◽  
Zou Xiaokang

This paper proposes a three-dimensional wireless sensor networks node localization algorithm based on multidimensional scaling anchor nodes, which is used to realize the absolute positioning of unknown nodes by using the distance between the anchor nodes and the nodes. The core of the proposed localization algorithm is a kind of repeated optimization method based on anchor nodes which is derived from STRESS formula. The algorithm employs the Tunneling Method to solve the local minimum problem in repeated optimization, which improves the accuracy of the optimization results. The simulation results validate the effectiveness of the algorithm. Random distribution of three-dimensional wireless sensor network nodes can be accurately positioned. The results satisfy the high precision and stability requirements in three-dimensional space node location.


2014 ◽  
Vol 716-717 ◽  
pp. 1322-1325
Author(s):  
Jin Tao Lin ◽  
Guang Yu Fan ◽  
Wen Hong Liu ◽  
Ying Da Hu

Sensor positioning is a fundamental block in various location-dependent applications of wireless sensor networks. In order to improve the positioning accuracy without increasing the complex and cost of sensor nodes, an improve sensor positioning method is proposed for wireless sensor networks. In the method, after receiving the broadcasting message of the neighboring anchor nodes, the sensor nodes calculate a modifying factor of the change of the signal strength. And they modify the distances between themselves and neighboring anchor nodes with the modifying factor. Simulation results show that the proposed method can obtain a high positioning accuracy.


2013 ◽  
Vol 475-476 ◽  
pp. 579-582 ◽  
Author(s):  
Dong Yao Zou ◽  
Teng Fei Han ◽  
Dao Li Zheng ◽  
He Lv

The node localization is one of the key technologies in wireless sensor networks. To the accurate positioning of the nodes as the premise and foundation, this paper presents a centroid localization algorithm based on Cellular network. First, the anchor nodes are distributed in a regular hexagonal cellular network. Unknown nodes collect the RSSI of the unknown nodes nearby, then select the anchor nodes whose RSSI is above the threshold. Finally, the average of these anchor nodes coordinates is the positioning results. MATLAB simulation results show that localization algorithm is simple and effective, it applies to the need for hardware is relatively low.


2014 ◽  
Vol 543-547 ◽  
pp. 3256-3259 ◽  
Author(s):  
Da Peng Man ◽  
Guo Dong Qin ◽  
Wu Yang ◽  
Wei Wang ◽  
Shi Chang Xuan

Node Localization technology is one of key technologies in wireless sensor network. DV-Hop localization algorithm is a kind of range-free algorithm. In this paper, an improved DV-Hop algorithm aiming to enhance localization accuracy is proposed. To enhance localization accuracy, average per-hop distance is replaced by corrected value of global average per-hop distance and global average per-hop error. When calculating hop distance, unknown nodes use corresponding average per-hop distance expression according to different hop value. Comparison with DV-Hop algorithm, simulation results show that the improved DV-Hop algorithm can reduce the localization error and enhance the accuracy of sensor nodes localization more effectively.


2021 ◽  
Author(s):  
Nour Zaarour ◽  
Nadir Hakem ◽  
NahiKandil

In wireless sensor networks (WSN) high-accuracy localization is crucial for both of WNS management and many other numerous location-based applications. Only a subset of nodes in a WSN is deployed as anchor nodes with their locations a priori known to localize unknown sensor nodes. The accuracy of the estimated position depends on the number of anchor nodes. Obviously, increasing the number or ratio of anchors will undoubtedly increase the localization accuracy. However, it severely constrains the flexibility of WSN deployment while impacting costs and energy. This paper aims to drastically reduce anchor number or ratio of anchor in WSN deployment and ensures a good trade-off for localization accuracy. Hence, this work presents an approach to decrease the number of anchor nodes without compromising localization accuracy. Assuming a random string WSN topology, the results in terms of anchor rates and localization accuracy are presented and show significant reduction in anchor deployment rates from 32% to 2%.


Sign in / Sign up

Export Citation Format

Share Document