In a mobile sensor network, a traditional positioning algorithm is unable to locate unknown nodes when losing anchor positions caused by communication interference. To solve this problem, an improved dv-hop algorithm ...
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In a mobile sensor network, a traditional positioning algorithm is unable to locate unknown nodes when losing anchor positions caused by communication interference. To solve this problem, an improved dv-hop algorithm based on a geometric Brownian motion (GBM) model was proposed including two main stages: location of sink node (LSN) and location of blind node (LBN). In the LSN stage, if the signal transmission of anchors is normal, the GBM model records the moving positions of the anchors. If not, the GBM model predicts the estimated average positions of the anchors using recorded data. Then, the trial count of the GBM model is optimized to further improve the prediction accuracy and computational overhead. In the LBN stage, the unknown nodes' positions are obtained by the dv-hop algorithm. In a traditional dv-hop algorithm, the approximate minimum hop number and average hop distance may lead to huge deviation between true position and estimated position. To improve the positioning accuracy in the LBN stage, the strategies of multi-communication radius and hop distance weighting were adopted. The simulation results demonstrated that the proposed algorithm has the capability to resist communication interference and adaptability at different node speeds , maintaining a relatively high accuracy in locating unknown nodes.
In order to improve the localization accuracy of unknown nodes in dv-hop algorithm, an improved dv-hop algorithm combined with adaptive hop count and optimized hop distance was proposed. Our proposed algorithm firstly...
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In order to improve the localization accuracy of unknown nodes in dv-hop algorithm, an improved dv-hop algorithm combined with adaptive hop count and optimized hop distance was proposed. Our proposed algorithm firstly introduced the concept of the adaptive value for the number of communication radii. It was used to adaptively select the number of communication radii for beacon nodes and could realize the subdivision of the minimum hop count. Secondly, sensor nodes adaptively set the hop threshold to reduce the calculation. Finally, the calculation method of the average hop distance of beacon nodes was optimized and the error was corrected. The average hop distance of unknown nodes was obtained by the weighted normalization used for the average hop distance of beacon nodes. Simulation results in both random deployment environment of sensor nodes and nonrandom deployment environment of beacon nodes demonstrate that the localization accuracy of our proposed algorithm is significantly better than the dv-hop algorithm and furthermore has better robustness and adaptability.
In view of the low precision of dv-hop positioning algorithm in wireless sensor network, an improved dv-hop localization algorithm that fuses chaotic sequences and Grey Wolf Optimization (GWO) algorithms is proposed. ...
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ISBN:
(数字)9781665458641
ISBN:
(纸本)9781665458641
In view of the low precision of dv-hop positioning algorithm in wireless sensor network, an improved dv-hop localization algorithm that fuses chaotic sequences and Grey Wolf Optimization (GWO) algorithms is proposed. Firstly, in order to reduce the average jump distance error, the algorithm introduces the correction factor, and secondly, for the cumulative calculation error brought about by the least squares method, the improved gray wolf optimization algorithm is used as an alternative, in order to further improve the positioning accuracy and convergence speed, the chaotic sequence is introduced to initialize the gray wolf population, adaptive adjustment strategy is applied to control parameter a, and the algorithm global search ability is improved by using random walking strategy. The simulation results show that compared with the traditional dv-hop algorithm, GA-dvhopalgorithm and PSO-dvhopalgorithm, the average positioning accuracy is improved by 90%, 86% and 78%.
The basic dv-hop algorithm can be simply implemented in real Wireless Sensor Networks without any range measurement tools, but it has bad localization accuracy. In this paper we present an advanced dv-hop algorithm. W...
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ISBN:
(纸本)9781538608432
The basic dv-hop algorithm can be simply implemented in real Wireless Sensor Networks without any range measurement tools, but it has bad localization accuracy. In this paper we present an advanced dv-hop algorithm. We tried to reduce the ranging error of dv-hop algorithm by two ways. Firstly, when the distance between two nodes is less than or equal to its communication radius, corresponding hops remember as 1 in basic dv-hop algorithm, the hop doesn't reflect distance between two nodes. So, hops are defined as continuous hops, and the paper names the continuous hops between beacon nodes by Euclidean distance. The paper define the continuous hops between others nodes by distance, which is measured by Shadowing model. Secondly, the average hop-size of the unknown nodes comes from a beacon node, but the nodes distribution is uneven in WSNs. We should fully use the information originated from more beacon nodes. The paper use trust degree of each beacon nodes to define the corresponding weighted value, after normalized weighted handing, the estimated hop-length of the unknown node is calculated. By simulation, we prove that advanced dv-hop algorithm performs a better localization accuracy compared with dv-hop algorithm, improved dv-hop algorithm (Chen et al. 2008) and improved dv-hop algorithm (Su Bing al. 2013), which is cause of better location accuracy.
Localization is one of the key technologies in wireless sensor networks. In this paper, the improved algorithm is derived from dv-hop algorithm, and uses entropy weight to improve localization accuracy without needing...
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ISBN:
(纸本)9783037852842
Localization is one of the key technologies in wireless sensor networks. In this paper, the improved algorithm is derived from dv-hop algorithm, and uses entropy weight to improve localization accuracy without needing an additional hardware device. Simulation results show that the improved dv-hop algorithm can provide more accurate location estimation than the dv-hop algorithm.
Node localization plays a fundamental role in wireless sensor networks (WSNs). The distance vector hop (dv-hop) algorithm is one of the best localization algorithms because of its low complexity, low cost, and simplic...
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ISBN:
(纸本)9781538607008
Node localization plays a fundamental role in wireless sensor networks (WSNs). The distance vector hop (dv-hop) algorithm is one of the best localization algorithms because of its low complexity, low cost, and simplicity. However, the localization accuracy can be poor when the number of anchor nodes is low. To improve this accuracy, a weighted dv-hop algorithm based on the received signal strength indicator (RSSI) is proposed. First, the RSSI is used to determine the fractional hops between nodes. Then a corrected average hop distance is obtained. Finally, unconstrained optimization is used to improve the localization accuracy. Performance results are presented for a log-normal shadowing channel which shows that the proposed algorithm is superior to the dv-hop and weighted dv-hop (Wdv-hop) algorithms.
In order to solve the problem of poor localization accuracy of dv-hop algorithm, an improved dv-hop algorithm is proposed in this paper. The proposed algorithm is based on RSSI technology to modify the hop count betwe...
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ISBN:
(纸本)9781479989201
In order to solve the problem of poor localization accuracy of dv-hop algorithm, an improved dv-hop algorithm is proposed in this paper. The proposed algorithm is based on RSSI technology to modify the hop count between nodes. The concept of basic signal strength of node which will be used to modify hop count is proposed in this paper. The hop coefficient and hopsize coefficient are set up to modify hop count and hop size of unknown nodes respectively. In addition, the packet life cycle is put forward to limit the transmission distance of network data packets. The simulation result shows that the proposed algorithm has better localization accuracy and can reduce the estimation error of hop count and hop size between nodes significantly.
In order to increase the indoor positioning accuracy and reduce the positioning error in wireless sensor network, the Bacterial Foraging Optimization algorithm is introduced to improve the dv-hop algorithm. The conven...
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ISBN:
(纸本)9781509028603
In order to increase the indoor positioning accuracy and reduce the positioning error in wireless sensor network, the Bacterial Foraging Optimization algorithm is introduced to improve the dv-hop algorithm. The conventional dv-hop algorithm is not very accurate in calculating the average distance per-hop, and it greatly affects the positioning accuracy. Hence, a new BFO-dv-hop (Bacterial Foraging Optimization dv-hop) algorithm is proposed in this paper. The conventional dv-hop algorithm calculates the average distance per-hop based on the Euclidean distance and the minimum number of hops directly, and the random distribution of the irregular network topology leads to the low accuracy in average hop distance estimation. In BFO-dv-hop algorithm, the average distance per-hop is calculated by the Bacterial Foraging Optimization algorithm (BFO) by using the minimum hops of nodes and the position information of anchor nodes. Simulation results show that 30% beacon anchors can effectively reduce the positioning error, and 10% beacon anchors can get a better performance compared with conventional algorithms.
The sensor node positioning is the important technology in Wireless Sensor Network. dv-hop algorithm has the accumulative errors during the sensor positioning procedure. In order to increase the dv-hop positioning pre...
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ISBN:
(纸本)9781479925650
The sensor node positioning is the important technology in Wireless Sensor Network. dv-hop algorithm has the accumulative errors during the sensor positioning procedure. In order to increase the dv-hop positioning precisions, this paper first corrects the distance of the average hop in dv-hop algorithm, then introduces cuckoo searching algorithm to optimize the sensor node positioning errors, and finally applies simulation experiment to test the performance. The simulation experiment illustrates the proposed algorithm needs extra hardware support in order to increase the Sensor positioning precisions compared to dv-hop algorithm. Even with fewer anchor nodes, the proposed algorithm can obtain ideal positioning results with high practical value.
This paper aims to improve the positioning accuracy of the traditional dv-hop algorithm in networks of uneven node distribution. For this purpose, an improved algorithm was proposed that reduces the errors in terms of...
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This paper aims to improve the positioning accuracy of the traditional dv-hop algorithm in networks of uneven node distribution. For this purpose, an improved algorithm was proposed that reduces the errors in terms of the hop count, the mean single-hop distance of anchor nodes and the mean single-hop distance of unknown nodes. Specifically, the hop count was modified based on the RSSI value of the node and the critical RSSI ratio;the mean single-hop distance of anchor nodes was corrected based on the ratio of the single-hop RSSI path length between two nodes to the mean single-hop RSSI path length (i.e. the correction factor);the mean single-hop distance of unknown nodes was divided into two sections to achieve better estimation of the distance between anchor nodes and unknown nodes. The simulation results indicate that the improved algorithm boasts better positioning accuracy and stability than the contrastive algorithms, with the addition of a few computing and communication overhead. The research findings shed new light on the accurate positioning of nodes in wireless sensor networks (WSNs).
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