Improved DV-Hop Algorithm Research Articles

Improved DV-Hop Algorithm Using Locally Weighted Linear Regression in Anisotropic Wireless Sensor Networks

The original DV-hop algorithm performs pretty well in isotropic Wireless Sensor Networks in which nodes distribute uniformly. However, the localization accuracy degrades severely in anisotropic networks caused by uneven nodal distribution or irregularity of deployment region. In this paper, we propose a novel DV-hop algorithm based on Locally Weighted Linear Regression (LWLR-DV-hop), in which kernel method is adopted to improve the localization accuracy by raising the weight of neighboring anchor nodes. In the simulation section, algorithms are evaluated within two deployments and three topologies: the regular and random deployments, the L-shaped, O-shaped and X-shaped topologies. As performance metrics, the Average Localization Error and the Cumulative Distribution Function are used. The results of simulation and experiment reveal that LWLR-DV-hop performs better than original DV-Hop in anisotropic networks of different topologies, in which localization accuracy is improved by about 40% on average.

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.

An Improved Three-dimensional DV-Hop Localization Algorithm Optimized by Adaptive Cuckoo Search Algorithm

Aiming at the low accuracy of DV-Hop localization algorithm in three-dimensional localization of wireless sensor network, a DV-Hop localization algorithm optimized by adaptive cuckoo search algorithm was proposed in this paper. Firstly, an improved DV-Hop algorithm was proposed, which can reduce the localization error of DV-Hop algorithm by controlling the network topology and improving the method for calculating average hop distance. Meanwhile, aiming at the slow convergence in traditional cuckoo search algorithm, the adaptive strategy was improved for the step search strategy and the bird's nest recycling strategy. And the adaptive cuckoo search algorithm was introduced to the process of node localization to optimize the unknown node position estimation. The experiment results show that compared with the improved DV-Hop algorithm and the traditional DV-Hop algorithm, the DV-Hop algorithm optimized by adaptive cuckoo search algorithm improved the localization accuracy and reduced the localization errors.

Research on Improved DV-HOP Algorithm against Wormhole Attacks in WSN

The secure location of node is significant in the WSN (Wireless Sensor Networks) of the troop frontier defence system. The wormhole attack is a big threat in the secure location. The credibility of the beacon node was used to determine the malicious nodes produced by wormhole attack in the WSN. The estimated method of multibeacon nodes was adopted to improve DV-HOP algorithm after excluding the malicious nodes. In this paper, we compared the basic DV-HOP algorithm and the improved DV-HOP algorithm in the coverage percentage and the error of network localization by simulating. The simulation results indicate that the improved DV-HOP algorithm makes the localization coverage percentage can reach 90% on a certain scale of the network, and it makes the error percentage lower when the number of beacons is different.

An Improved DV-Hop Localization Algorithm Against Wormhole Attack in WSN

Wormhole attack is one of the most serious attacks on DV-Hop localization algorithm. Previous solutions usually require hardware support, or a higher ratio of beacon nodes and very complex mathematical operations. In this paper, we analyze the effect of the wormhole attack on DV-Hop algorithm, which mainly destroys the network topological structure and shrinks hop count between nodes and expands the localization error. We propose a modified DV-Hop method without additional hardware support against wormhole attacks. Through analyzing the characteristics of the neighboring nodes set of nodes attacked, this method detects wormhole attack, then locates nodes by using an improved DV-Hop algorithm. We show that the scheme can detect wormhole attacker adequately, and the obtained localization accuracy is even better than that of the DV-Hop method without wormhole attacks in most cases.

Research on the Positioning in WSN Based on an Improved DV-HOP Algorithm

In order to reduce the positioning error of the sensor nodes, this paper first analyzes the reasons for the low accuracy of DV - HOP algorithm currently, and then proposes an improved DV - HOP algorithm. The algorithm can be divided into four stages, including data information overlapping stage, average skip distance calculation stage, optimum choice of anchor nodes and redundant node positioning. In the data information overlapping stage, the joint probability density is used for improvement; in the average skip distance calculation, the zero deviation estimation value is introduced; in the optimal selection of anchor nodes, optimal strategy is used; and the nodes are positioned in the redundant node positioning with the method of gradually increasing the skip distance. Simulation results show that the algorithm of this paper can effectively reduce the position error in calculation and improve the positioning accuracy.

Application of an Improved DV-HOP Algorithm in WSN

Application of an Improved DV-HOP Algorithm in WSN

Improved DV-Hop Algorithm Based on Artificial Bee Colony

Improved DV-Hop Algorithm Based on Artificial Bee Colony

An Improved DV-Hop Algorithm Based on Shuffled Frog Leaping Algorithm

According to that node localization accuracy is not high in the DV Hop localization algorithm, shuffled frog leaping algorithm with many advantages such as the convergence speed is fast, easy to realize and excellent performance of global optimization and so on is introduced into the design of DV-Hop algorithm. A new DV-Hop algorithm based on shuffled frog leaping algorithm (Shuffled Frog Leaping DV-Hop Algorithm, SF LA DV-Hop) is proposed in this paper. Based on traditional DV-Hop algorithm, the new algorithm used distance of nodes and position information of anchor nodes to establish objective optimization function and realize the estimation of unknown node coordinate in the final stage of DV-Hop algorithm. The simulation results showed that compared with the traditional DV-Hop algorithm, based on not increasing the sensor node hardware overhead, the improved algorithm can effectively reduce the positioning error.

An Improved DV-Hop Algorithm for Resisting Wormhole Attack

As DV-Hop algorithm estimates distance by distance vector exchanging, positioning process is vulnerable to devastate wormhole attacking. An improved DV-Hop algorithm (AWADV-Hop) which resists wormhole attack is proposed, based on the original algorithm in this paper. To solve the problem that hops and the average distance per hop is the most vulnerable to wormhole attack in DV-Hop. This paper first fixes hop value by detecting the wormhole attack. Then, according to error comparison of the average distance per hop of anchor node and the average distance per hop of the whole network, locate permission of anchor nodes are re-decided. Average distance per hop of anchor nodes with positioning permissions is weighted to be the ultimate per hop distance of unknown node. Finally, simulated by MATLAB and simulation results show that this algorithm can effectively resist wormhole attack and improve the positioning accuracy.

Position Location Scheme Using Nonlinear Programming Based on RSSI and DV-Hop

Localization is used in location-aware applications such as navigation, autonomous robotic movement, and asset tracking to position a moving object on a coordinate system. In this paper, a Nonlinear Programming algorithm is proposed based on RSSI and improved DV-Hop algorithm, called NPRDV-Hop. The algorithm makes four major contributions to the localization problem in the wireless sensor networks (WSNs). Firstly, a hop distance is improved, called Hop Distance. This scheme could assure that the most nodes receive the Hop Distance from beacon node who has the least hops between them. This practical localization scheme is relatively high accuracy and low cost for WSNs. Secondly, Heron's formula is introduced as objective function. Thirdly, Gauss distribution is introduced to select RSSI so that the error of distance is little. Lastly, the general problem is considered by the nonlinear programming to solve for the locations of the sensors. Simulation results show that the proposed method can improve location accuracy and coverage without increasing hardware cost of sensor node. The performance of this algorithm is superior to the original DV-Hop algorithm.

Improvements of DV-Hop localization algorithm for wireless sensor networks

Based on the improvements of the original DV-Hop localization algorithm, three new localization algorithms (iDV-Hop1, iDV-Hop2, and Quad DV-Hop) are presented in this article. In iDV-Hop1 and iDV-Hop2, all steps of the original DV-Hop are kept, and several steps based on geometry improvements of the localization problem are added in order to obtain better localization accuracy. The third algorithm (Quad DV-Hop) formulated the localization problem as bounded least squares problem, to be solved by quadratic programming. Simulations are carried out on the four different types of network topology by varying nodes communication range, number of anchor nodes and number of nodes. Comparison of our algorithms with the original DV-Hop and Improved DV-Hop algorithms are given. It is shown that iDV-Hop1 algorithm can significantly reduce the localization error (up to three times) in scenarios with irregular topologies compared to DV-Hop and Improved DV-Hop. In scenarios with regular topologies, iDV-Hop2 and Quad DV-Hop showed better performance compared to DV-Hop and Improved DV-Hop (up to 11 % lower localization error).

An improved localization algorithm based on genetic algorithm in wireless sensor networks.

Wireless sensor network (WSN) are widely used in many applications. A WSN is a wireless decentralized structure network comprised of nodes, which autonomously set up a network. The node localization that is to be aware of position of the node in the network is an essential part of many sensor network operations and applications. The existing localization algorithms can be classified into two categories: range-based and range-free. The range-based localization algorithm has requirements on hardware, thus is expensive to be implemented in practice. The range-free localization algorithm reduces the hardware cost. Because of the hardware limitations of WSN devices, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. However, these techniques usually have higher localization error compared to the range-based algorithms. DV-Hop is a typical range-free localization algorithm utilizing hop-distance estimation. In this paper, we propose an improved DV-Hop algorithm based on genetic algorithm. Simulation results show that our proposed algorithm improves the localization accuracy compared with previous algorithms.

Optimization of DV-hop localization algorithm in hybrid optical wireless sensor networks

Automatic localization is one of the major issues in Wireless Sensor Networks (WSN). DV-hop algorithm is a well-known localization algorithm in WSN but with limited localization accuracy. In this paper, an improved DV-hop localization algorithm in hybrid optical wireless sensor networks is proposed based on the optimization of the parameters in WSN. Various factors that affect the localization accuracy of the DV-hop algorithm in WSN are investigated, including the communication radius of the node, the number of beacon nodes and the number of the total nodes. As the DV-hop algorithm is applied into hybrid optical sensor and WSNs (O-WSN) with rectangular topology, different parameters have to be optimized accordingly. Simulation results show that the square topology outperforms the rectangle topology more than 45 % under the same network parameters using the improved DV-hop algorithm. Therefore another improved DV-hop called Sub-Square Weighted DV-hop (SSW DV-hop) is proposed for the rectangle topology. Both simulation and experiment results demonstrate that applying the SSW DV-hop algorithmin O-WSNs could significantly improve the localization accuracy.

Improved DV-Hop Algorithm for Enhancing Localization Accuracy in WSN

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.

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

The node localization technology of wireless sensor networks is essential and prerequisite to many applications, which it is one of the important support technologies for wireless sensor networks. The node localization is to get the position information of blind node by using location information of few known nodes and some special mechanisms. This paper primarily investigates a kind of target localization technology based on the improved DV-Hop algorithm in wireless sensor networks. We firstly compute the distances measured by RSSI and the mean value of one-hop distance. Then we can use the differences between the mean and the actual distance to get the error correction between the total distance and average one-hop distance. Replace trilateration with hybrid localization of MIN-MAX and weighted least square method. Finally, simulation experiment results show the improved algorithm can effectively carry out the network localization, thus has a certain of practical value

Positioning Research for Wireless Sensor Networks Based on PSO Algorithm

Based on the traditional DV-Hop algorithm and in order to overcome its existing drawbacks, an improved DV-Hop algorithm is brought forward in this paper by using the PSO algorithm. Through simulation experiments, it is found that both the average localization error and the localization coverage rate of PSO are better than that of DV-Hop. Moreover, with the increase of the number of nodes, the average localization error of PSO shows a downward trend and is less than that of DV-Hop. DOI: http://dx.doi.org/10.5755/j01.eee.19.9.5522

An Improvement of Localization Algorithm Based on Particle Swarm Optimization and Simulated Annealing in Wireless Sensor Networks

The node localization is an important problem in wireless sensor networks. The localization schemes are categorized into range-based and range-free, depending on whether the distance or angle estimation is used. DV-Hop is a typical range-free localization algorithm using hop-distance estimate with relatively high average localization error. In this paper, we propose an improved DV-Hop algorithm based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) with no additional hardware support. Compared to the DV-Hop algorithm and the improved DV-Hop based on PSO, the proposed algorithm has less average localization error and reduces the cost effectively.

DV-Hop Localization Algorithm in WSN Based on Weighted of Correction in Hop Distance

Because of the DV-Hop algorithm has a big error in the estimation of the average hop distance, this paper proposed a weighted hop distance correction localization algorithm. The improved algorithm is carried out by introducing the average hop distance error correction value of the weighting processing, thereby reducing the hop distance error, and avoid the accumulation of errors in the subsequent computation process. The simulation results show that the improved DV-Hop algorithm reduces localization error effectively and has good stability without additional devices; therefore, it is a practical localization solution for WSN.

Study on Navigation of Wireless Sensor Network Mobile Robot

For optimal design of mobile robot path planning problem, an improved artificial potential field control method is designed. Using infrared sensors and ultrasonic sensors to detect the surrounding environment will get the information of obstacles and goals. Proposed an adaptive real-time localization algorithm based on improved DV-Hop algorithm to realize real-time localization for wireless sensor network mobile robot. The improved artificial potential field adopted the improved potential function that ensured the goal is the global minimum so the mobile robot can reach the goal freely. The effectiveness and feasibility of the improved algorithm verified by simulation.