Distance Vector Hop Algorithm Research Articles

A Hybrid Approach Using Multistage Collaborative Calibration for Wireless Sensor Network Localization in 3D Environments

Accurate localization is critical in the internet of things (IOT), especially for wireless sensor networks (WSNs). Location estimation can be affected by factors such as node density, topological diversity, and sensor coverage. As such, we propose a hybrid approach using multistage collaborative calibration for wireless sensor network localization, specifically in 3D environments. This technique integrates a Modified version of Light Gradient Boosting Model (MLGB), which is based on a regression scheme, a cooperative methodology, and a fine calibration model for collaborative fusion. These techniques were combined with quadrilateral shrunk centroid (QSC) and distance vector hop algorithms, using a multi-communication radius and an improved frog-leaping algorithm (DVMFL). In the first step, MLGB was used to correct for inhomogeneous localization estimation errors and RSSI data sparsity. As a result, the model is capable of adapting to high topological diversity (i.e., C-shape, H-shape, S-shape, and O-shape).Successive steps further improved prediction accuracy by using a screening cooperative anchor node strategy to increase node density and enhance the QSC-DVMFL fusion framework for fine position estimation. The proposed methodology was assessed in a series of validation, comparing it to other techniques. The results demonstrated a clear effectiveness and adaptability across a variety of factors that typically affect WSN localization.

Flood Control Distance Vector-Hop (FCDV-Hop) Localization in Wireless Sensor Networks

Distance Vector-Hop (DV-Hop) localization is a distributed, hop by hop positioning algorithm. Anchor nodes generate the packets of nodes position information to calculate the number of hops between the beacon nodes and the anchor nodes, and these packets are flooded in the respective Wireless Sensor Networks (WSN). The DV-Hop algorithm obtains the distance information from the unknown nodes to the anchor nodes through the network topology calculation rather than the radio wave signals measurement which are used in the range-based algorithm. However, flooding information from all anchors to all beacon nodes will become too expensive for large networks (i.e., cost, energy), even with low anchor fraction. The region of nodes flooding through the network needs to be confined within logical constraints to produce better accuracy to reduce the localization error while reducing the cost. This research proposes and develops an enhanced algorithm that can improve the region area for sensor nodes placement within the specific localization area. This research aims to produce a longer network lifetime by reducing the energy used of the sensor nodes and at the same time minimize the localization error. This research describes the flooding control of the node's placement for the localization of the DV-Hop algorithm. The placement of nodes is limited inside the region of the anchor nodes. The simulation environment setup comes with parameters such as the radius, area, number of nodes, types of nodes, the anchor proportion, and the value of the regions. The result shows an improvement for the localization error, the power consumption, and the accuracy of the nodes positioning.

An Enhanced Distance Vector-Hop Algorithm using New Weighted Location Method for Wireless Sensor Networks

Location is an indispensable segment for Wireless Sensor Network (WSN), since when events happened, we need to know location. The distance vector-hop (DV-Hop) technique is a popular range-free localization algorithm due to its cost efficiency and non-intricate process. Nevertheless, it suffers from poor accuracy, and it is highly influenced by network topology; Especially, more hop counts lead to more errors. In the final phase, least squares are employed to address nonlinear equation, which will gain greater location errors. Aimed at addressing problems mentioned above, an enhanced DV-Hop algorithm based on weighted factor, along with new weighted least squares location technique, is proposed in this paper, and it is called WND-DV-Hop. First, the one hop count of unknown node was corrected by employed received signal strength indication (RSSI) technology. Next, in order to reduce average hop distance error, a weighted coefficient based on beacon node hop count was constructed. A new weighted least squares method was embedded to solve nonlinear equation problem. Finally, considerable experiments were carried out to estimate the performance of WND-DV-Hop, compared the outcomes with state-of-the-art DV-Hop, IDV-Hop, Checkout-DV-Hop, and New-DV-Hop depicted in literature. The empirical findings demonstrated that WND-DV-Hop significantly outperformed other localization algorithms.

Fast triangle flip bat algorithm based on curve strategy and rank transformation to improve DV-Hop performance

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm’s performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

Research of localization algorithm for wireless sensor network based on DV-Hop

Wireless sensor network (WSN) possesses very broad application prospect in many fields, where the node location technology is one of the key technologies of WSN. Distance vector hop (DV-Hop) localization algorithm is a widely used algorithm in this technology, and it uses routing exchange protocol to make unknown nodes obtain beacon node information which will be used for coordinate calculation, therefore there exists certain error for the algorithm itself. Aiming at the disadvantage of large error existing in the traditional wireless sensor network location algorithm based on DV-Hop, an improved DV-Hop algorithm based on hop thinning and distance correction is proposed. The minimum hop is corrected by introducing received signal strength indication (RSSI) ranging technology, and the average hop distance is corrected by weighted average value of hop distance error and estimated distance error. Subsequently, the overall improvement on the location performance of the Hop-DV location algorithm is realized, and the location error is reduced. Under the Matlab simulation environment, the simulation experiment on the improved algorithm is carried out. The experimental results show that the improved algorithm reduces the location error and has higher location accuracy.

Improvement of DV-Hop localization algorithm for randomly deployed wireless sensor networks

The Distance Vector-Hop (DV-Hop) algorithm is a well-known technique for wireless sensor networks node location due to its robustness, simplicity and cost effectiveness. Therefore scientists are still searching for its improvement. Aiming at optimizing the localization accuracy in traditional DV-Hop algorithm, we propose a novel improved recursive DV-Hop localization algorithm in this paper. Our research focuses on range-free localization algorithm in homogeneous multi-hop wireless sensor networks. The proposed algorithm is based on a recursive position calculation of unknown nodes. It also focuses on second and third step of DV-Hop algorithm. We aim to use an optimized formulation to calculate the average hop-size of anchor nodes aiming to minimize the localization error in the estimated distance between anchor and unknown node, thus achieving better localization accuracy. Simulation results prove the performance of our proposed algorithm comparing with DV-Hop algorithm and DV-Hop based algorithms in different deployment scenarios.

Hop-Count Quantization Ranging and Hybrid Cuckoo Search Optimized for DV-HOP in WSNs

Localization technology occupies a very important position in wireless sensor network (WSN). Distance vector-hop (DV-HOP) algorithm is range-free localization algorithm and has advantages of low overhead and can handle the case where a normal node has less than three neighbor anchors. However, considering the problem of high localization error of DV-HOP algorithm in WSN. An hybrid DV-HOP localization algorithm based on hop-count quantization anchor and modified cuckoo search (HMCS-D) is proposed. The algorithm using the correction factor to correct the number of hops that can reduce the error caused by the recording inaccurate minimum hops. The nodes of the hop neighbor nodes in the network are divided into three disjoint subsets and the distance between the nodes is estimated according geometric method. Then according to the weight of each anchor node to select average jump distance of unknown nodes. Finally, introduced hybrid cuckoo search which can dynamically adjust the search step size and using the search algorithm to calculate the node coordinates instead of the maximum likelihood estimation method. Simulation results show that compare with DV-HOP and cuckoo search DV-HOP algorithm, the average positioning error of HMCS-D algorithm decrease 39.7%, 10.6% respectively. Prove that the HMCS-D algorithm effectively improve the node localization accuracy, reduce the positioning error and without affecting the hardware cost.

On Improved DV‐Hop Localization Algorithm for Accurate Node Localization in Wireless Sensor Networks

Node Localization is a fundamental issue for many critical applications in Wireless sensor networks (WSNs). Traditional DV-Hop localization algorithm and corresponding improved ones still cannot provide su.cient localization accuracy in such WSNs. To ensure accurate localization, this paper proposes an improved DistancevectorHop (DV-Hop) localization algorithm. Under such an algorithm, we determine a corrected average hopdistance of beacon nodes by employing the di.erences between actual and estimated distance among beacon nodes in WSNs. We propose a probability information based selective strategy for the selection of beacon nodes. Based on these selected beacon nodes, we adopt a two dimensional hyperbolic function to predict the locations of unknown nodes. Simulation results are provided to illustrate the localization accuracy of our algorithm compared with traditional DV-Hop algorithm and its two improved algorithms in WSNs.

Improved DV-Hop Localization Algorithm Based on Dynamic Anchor Node Set for Wireless Sensor Networks

Node localization is a key issue in wireless sensor networks (WSN) area, and distance vector hop (DV-Hop) algorithm is widely adopted in WSN localization. Existing DV-Hop based algorithms employ all anchor nodes to localize the unknown node. However there is a large error of the estimated distance from the unknown node to some anchor nodes, which also results in the final unknown node localization error large. To improve the localization accuracy, we propose an improved DV-Hop algorithm based on dynamic anchor node set (DANS IDV-Hop). Differently to the existing DV-Hop based algorithms which apply total anchor nodes, DANS IDV-Hop utilizes part of anchor nodes to participate in localization. Firstly, the selection of anchor nodes is abstracted into a combinatorial optimization problem. For selecting appropriate anchor nodes, a novel binary particle coding scheme and fitness function are designed. Subsequently, the binary particle swarm optimization (BPSO) algorithm is applied to construct the dynamic anchor node set (DANS), and the localization is carried out on the DANS. Finally, the continuous particle swarm optimization (PSO) algorithm is utilized to further optimize the unknown node coordinates. Simulation results show that DANS IDV-Hop has excellent localization accuracy than that of the original DV-Hop and other DV-Hop based improved algorithms.

A novel DV-Hop method based on coupling algorithm used for wireless sensor network localisation

Wireless Sensor Network (WSN) localisation is an essential requirement in the increasing prevalence of WSN applications. It is an important part of the Internet of Things (IOT) and has become a hot research area. Distance Vector-Hop algorithm (DV-Hop), a range-free algorithm, is widely deployed to solve the localisation problem in WSN. However, the results of the estimation precision are usually not satisfactory. In order to improve the WSN positioning accuracy, in this paper, we propose a new coupling algorithm based on Bacterial Foraging Algorithm (BFA) and Glow-worm Swarm Optimisation (GSO) (BFO-GSO). The algorithm has good convergence speed, local search ability of BFO and global convergence of GSO. The optimisation performance is verified by CEC2013 benchmarks in those designs against the original algorithm. Furthermore, Wilcoxon's rank-sum non-parametric statistical test and Friedman test are carried out to judge whether the results of the proposed algorithm differ from those of the other algorithms in a statistically significant way. The numerical results prove that it is able to significantly outperform others on majority of the benchmark functions. Finally, the proposed algorithm is also combined into the DV-Hop algorithm to improve the WSN positioning accuracy. Experimental results show that our improved algorithm achieves better performance when compared with other DV-Hop algorithms.

A Novel WSN-Oriented Locating Approach Based on Density

It is known that the locating accuracy of the traditional Distance Vector-HOP (DV-HOP) approach in a Wireless Sensor Network (WSN) depends on the density of the anchor node. A novel WSN-oriented locating approach based on a node's density is proposed in this paper. The approach can compute the distance of the node based on the maximum likelihood estimation strategy. It can improve the accuracy ratio of the measuring distance among the nodes. The relative nodes of a WSN can find the average hop distances by estimating the distances from themselves to their circular nodes. In order to assess the performance of the approach, the belief degree of locating is computed based on the possibility theory by our suggested fusion mechanism. This is a feasible method to solve the dependence problem of the DV-HOP algorithm on the anchor node density. Results of many simulation tests of the application show that our proposed WSN-oriented locating approach based on node density can improve the accuracy ratio of the measuring distance and the correctness of locating.

A Hybrid DV-Hop Algorithm Using RSSI for Localization in Large-Scale Wireless Sensor Networks.

With the increasing realization of the Internet-of-Things (IoT) and rapid proliferation of wireless sensor networks (WSN), estimating the location of wireless sensor nodes is emerging as an important issue. Traditional ranging based localization algorithms use triangulation for estimating the physical location of only those wireless nodes that are within one-hop distance from the anchor nodes. Multi-hop localization algorithms, on the other hand, aim at localizing the wireless nodes that can physically be residing at multiple hops away from anchor nodes. These latter algorithms have attracted a growing interest from research community due to the smaller number of required anchor nodes. One such algorithm, known as DV-Hop (Distance Vector Hop), has gained popularity due to its simplicity and lower cost. However, DV-Hop suffers from reduced accuracy due to the fact that it exploits only the network topology (i.e., number of hops to anchors) rather than the distances between pairs of nodes. In this paper, we propose an enhanced DV-Hop localization algorithm that also uses the RSSI values associated with links between one-hop neighbors. Moreover, we exploit already localized nodes by promoting them to become additional anchor nodes. Our simulations have shown that the proposed algorithm significantly outperforms the original DV-Hop localization algorithm and two of its recently published variants, namely RSSI Auxiliary Ranging and the Selective 3-Anchor DV-hop algorithm. More precisely, in some scenarios, the proposed algorithm improves the localization accuracy by almost 95%, 90% and 70% as compared to the basic DV-Hop, Selective 3-Anchor, and RSSI DV-Hop algorithms, respectively.

Nature Inspired Algorithm-Based Improved Variants of DV-Hop Algorithm for Randomly Deployed 2D and 3D Wireless Sensor Networks

Localization is a significant challenge in the area of wireless sensor networks (WSNs). Distance Vector Hop (DV-Hop) algorithm is most preferable algorithm due to its low cost, distributed nature, and its feasibility for all kinds of sensor networks, but it suffers from high localization error. In order to reduce the problem of high localization error for 2-dimensional and 3-dimensional WSNs, two Nature Inspired Algorithm based improved variants have been proposed. The first one uses Grey-Wolf optimization (GWO-DV-Hop) to identify a better estimate of average distance per hop and second one, a weighted Grey-Wolf optimization (Weighted GWO-DV-Hop), finds average distance per hop as computed by each beacon node using grey wolf algorithm and then, a weighted approach is applied by each node to get weighted average distance per hop (weights based on distance from each beacon) so as to consider impact of all types of beacons. The results prove the superiority of proposed algorithms over traditional DV-Hop in terms of localization error.

An improved distance vector-Hop localization algorithm based on coordinate correction

In order to improve the localization accuracy of distance vector-Hop algorithm under the random topology network scenarios, a novel algorithm named coordinates correction-distance vector-Hop is pro...

Modified Energy-Efficient Range-Free Localization Using Teaching–Learning-Based Optimization for Wireless Sensor Networks

ABSTRACTThis paper presents an energy-efficient Modified Distance Vector Hop algorithm using Teaching–Learning-Based Optimization, viz. MDV-TLBO, which is range-free, distributed localization algorithm for wireless sensor network (WSN). In the proposed algorithm, the hop size of anchor node is modified by adding correction factor. The concept of collinearity is introduced in this paper to reduce location errors caused by anchor nodes which are collinear. TLBO is used to enhance the localization accuracy, which is parameter-free, efficient optimization technique. Target nodes estimate their final coordinates after location upgradation procedure. In MDV-TLBO, anchor nodes communicate only one time with target nodes to broadcast their location. Hop size modification, optimal selection of anchor nodes, location optimization, and location upgradation are done at target node level, resulting considerable reduction in communication between nodes, due to which energy consumption of the nodes has been significantly reduced. To show the applicability of proposed algorithm in real scenarios, radio irregularity model is considered. Simulation results show that our proposed algorithm achieves better localization accuracy, high positioning coverage with less energy consumption in comparison of the existing improved DV-Hop algorithms.

Novel Positioning Service Computing Method for WSN

The challenge of wireless sensor network (WSN) becomes truly pervasive is that of reliable positioning problem. The positioning accuracy of the traditional DV-HOP (Distance Vector-HOP) algorithm has very strong dependence for density of anchor node, only when anchor node density reaches a certain extent, will it has better positioning effect. Therefore, it increases the cost of network service. In this paper, we propose novel positioning service computing method for WSN. The method can estimate distance of nodes which has same neighbor nodes by maximum likelihood estimation. It effectively improves the accuracy of measuring distance among nodes. The nodes can obtain itself average hop distance by the distance from itself to its circular nodes and the number of jump. It's a good solution to solve the dependence of traditional DV-HOP algorithm on anchor node density. In the positioning service stage, based on intersection density among circles with anchor node as center and estimation distance as radius, the method can replace triangle positioning algorithm by the method of estimating the node coordinates to be measured. The belief degree of reliable positioning service can be computed by our proposed fusion method. Our experiments show that our presented method can solve the problem of estimated error of distance caused by loop and it can greatly improve the efficiency of positioning service.

The Performance Evaluation of Hybrid Localization Algorithm in Wireless Sensor Networks

As one of the key techniques in wireless sensor networks (WSN), localization algorithm has been a research hot topic and indispensable function in most wireless applications. In order to promote localization accuracy and efficiency, a lot of localization algorithms with different performances and computation complexities have been proposed. The paper discusses the drawbacks of some typical works on localization, and proposes a hybrid localization algorithm integrated with approximate point in triangle (APIT) and distance vector-hop (DV-HOP). To address the positioning accuracy and coverage rate, the objectives of this paper are three folds: firstly, adopting angle detection to determine the exact direction of unknown nodes. Then, the APIT algorithm is adopted over all unknown nodes within the triangle and its localization error is reduced from 14.7215 m in conventional APIT to 3.2348 m in the considered scenario. Finally, the DV-HOP algorithm is adopted with different weights for the nodes within the minimum hops, and localizes the rest unknown nodes in WSN with localization accuracy increased by 49%.

Improved DV-Hop Localization Algorithm Based on Bat Algorithm in Wireless Sensor Networks

Obtaining accurate location information is important in practical applications of wireless sensor networks (WSNs). The distance vector hop (DV-Hop) is a frequently-used range-free localization algorithm in WSNs, but it has low localization accuracy. Moreover, despite various improvements to DV-Hop-based localization algorithms, maintaining a balance between high localization accuracy and good stability and convergence is still a challenge. To overcome these shortcomings, we proposed an improved DV-Hop localization algorithm based on the bat algorithm (IBDV-Hop) for WSNs. The IBDV-Hop algorithm incorporates optimization methods that enhance the accuracy of the average hop distance and fitness function. We also introduce a nonlinear dynamic inertial weight strategy to extend the global search scope and increase the local search accuracy. Moreover, we develop an updated solutions strategy that avoids premature convergence by the IBDV-Hop algorithm. Both theoretical analysis and simulation results show that the IBDV-Hop algorithm achieves higher localization accuracy than the original DV-Hop algorithm and other improved algorithms. The IBDV-Hop algorithm also exhibits good stability, search capability and convergence, and it requires little additional time complexity and energy consumption.

An Advanced DV-hop Localization Algorithm in Wireless Sensor Network

Position information is a fundamental element in WSN. As one of the range-free localization algorithm, the DV-Hop (Distance Vector-Hop) is widely applied. The DV-Hop localization algorithm employs the physical distance between the anchor nodes to estimate the average hop distance, instead of the actual transmission distance. The distance gap between the two kinds of distance undoubtedly leads to the error of the average hop distance as well as relatively high localization error. Aiming at solving the problem, the improved algorithm is proposed. The reason of error between the physical distance and actual transmission distance is analyzed in the paper, and summarized as the asymmetry of distance resulted from the nodes random distribution, as well as the deviation degree between the actual transmission path and the physical distance，and the distance compensation model is built based on the asymmetry and deviation degree to make the physical distance closer to the transmission distance . In the improved algorithm increases no extra hardware and complexity. Compared to the original DV-Hop algorithm, the simulation results show that the improved algorithm proposed in the paper increases the positioning accuracy of the unknown nodes. Keyword: Wireless Sensor Network; Positioning Algorithm; nonuniformity; nonlinear degree; topological structure; DV-Hop

Power efficient range-free localization algorithm for wireless sensor networks

Considering energy consumption, hardware requirements, and the need of high localization accuracy, we proposed a power efficient range-free localization algorithm for wireless sensor networks. In the proposed algorithm, anchor node communicates to unknown nodes only one time by which anchor nodes inform about their coordinates to unknown nodes. By calculating hop-size of anchor nodes at unknown nodes one complete communication between anchor node and unknown node is eliminated which drastically reduce the energy consumption of nodes. Further, unknown node refines estimated hop-size for better estimation of distance from the anchor nodes. Moreover, using average hop-size of anchor nodes, unknown node calculates distance from all anchor nodes. To reduce error propagation, involved in solving for location of unknown node, a new procedure is adopted. Further, unknown node upgrades its location by exploiting the obtained information in solving the system of equations. In mathematical analysis we prove that proposed algorithm has lesser propagation error than distance vector-hop (DV-Hop) and other considered improved DV-Hop algorithms. Simulation experiments show that our proposed algorithm has better localization performance, and is more computationally efficient than DV-Hop and other compared improved DV-Hop algorithms.