Chunyu Miao

Collaborative Localization and Location Verification in WSNs

Localization is one of the most important technologies in wireless sensor networks. A lightweight distributed node localization scheme is proposed by considering the limited computational capacity of WSNs. The proposed scheme introduces the virtual force model to determine the location by incremental refinement. Aiming at solving the drifting problem and malicious anchor problem, a location verification algorithm based on the virtual force mode is presented. In addition, an anchor promotion algorithm using the localization reliability model is proposed to re-locate the drifted nodes. Extended simulation experiments indicate that the localization algorithm has relatively high precision and the location verification algorithm has relatively high accuracy. The communication overhead of these algorithms is relative low, and the whole set of reliable localization methods is practical as well as comprehensive.

3D Self-Deployment Algorithm in Mobile Wireless Sensor Networks

The sensor deployment problem of wireless sensor networks (WSNs) is a key issue in the researches and the applications of WSNs. Fewer works focus on the 3D autonomous deployment. Aimed at the problem of sensor deployment in three dimensional spaces, the 3D Self-Deployment Algorithm (3DSD) in mobile sensor networks is proposed. A 3D virtual force model is utilized in the 3DSD method. A negotiation tactic is introduced to ensure network connectivity, and a density control strategy is used to balance the node distribution. The proposed algorithm can fulfill the nodes autonomous deployment in 3D space with obstacles. Simulation results indicate that the deployment process of 3DSD is relatively rapid, and the nodes are well distributed. Furthermore, the coverage ratio of 3DSD approximates the theoretical maximum value.

3D self-deployment algorithm in mobile wireless sensor networks

The sensor deployment problem of wireless sensor networks (WSNs) is a key issue in the researches and the applications of WSNs. Fewer works focus on the 3D autonomous deployment. Aimed at the problem of sensor deployment in three-dimensional spaces, the 3D self-deployment (3DSD) algorithm in mobile sensor networks is proposed. A 3D virtual force model is utilized in the 3DSD method. A negotiation tactic is introduced to ensure network connectivity, and a density control strategy is used to balance the node distribution. The proposed algorithm can fulfill the nodes autonomous deployment in 3D space with obstacles. Simulation results indicate that the deployment process of 3DSD is relatively rapid and the nodes are well distributed. Furthermore, the coverage ratio of 3DSD approximates the theoretical maximum value.

Study on Tree-Based Clustering MDS Algorithm for Nodes Localization in WSNs

Localization of sensors nodes is a key and fundamental issue in WSNs due to random deployment. In this paper, we propose a tree based clustering (TBC) multidimensional scaling algorithm for wireless sensor networks with the purpose of overcoming the shortage of classical MDS algorithms in its localization accuracy and computing complexity. Clustering is adopted to degrade the problem scale in our approach and a moderate number of common nodes between clusters are kept during clustering. Inner cluster local coordinates are calculated and then mapped into global coordinates according the tree structure formed by clustering. The simulations on MATLAB are conducted and the results show that the proposed algorithm has better localization coverage and higher accuracy than the traditional MDS based algorithms.

Cooperative Localization and Location Verification in WSN

Localization is one of the most important technologies in wireless sensor networks. A lightweight distributed node localization scheme is proposed by considering WSNs’ limited computational capacity. The proposed scheme uses the virtual force model to get the location by incremental refinement. Aiming at solving the anchor drifting problem and malicious anchor problem, using sensor node mutual observation principle, a location verification algorithm based on the same computation model as localization process is presented. Extended simulation experiments indicate that the localization algorithm has relatively high precision and the location verification algorithm has relatively high accuracy. The communication overhead of these algorithms is relative low, and the whole set of reliable localization methods are practical.

A Node Localization Verification Model for WSN

Localization is one of the most important technologies in wireless sensor networks. Range-based localization methods are widely used in many applications. However, traditional RSS-based methods cannot work well in scenarios with unreliable anchors. A reputation scheme based distributed location verification model called UNDA is proposed to solve the unreliable node recognizing issue in such scenarios. UNDA combines direct reputation and third-party reputation to recognize unreliable anchor. Furthermore, a credibility-updating scheme is presented to make the third-party reputation more accuracy. Extensive simulation experiments indicate that the location verification algorithm has relatively high accuracy as well as low communication overhead, and the convergence of UNDA is rapid. The UNDA can be a used as an underlayer for traditional RSS-based localization algorithms to realize reliable localization.

RI-MDS: multidimensional scaling iterative localization algorithm using RSSI in wireless sensor networks

To improve the feasibility and the convenience of localization methods for wireless sensor networks, a localization algorithm RI-MDS (RSSI-based iterative-multidimensional scaling) is proposed. The RI-MDS method is centralized and mainly focuses on improving localization accuracy. It collects RSSI vectors as ranging basis and combines the metric MDS method and the nonmetric MDS method to accomplish the relative localization. Then it uses the maximum likelihood method in affine transformation to transform the relative coordinates to absolute ones. Our method has no need for additional equipment on the WSN nodes. Simulation and field experiments show that the average localization error and the localization error ratio of the RI-MDS method are relatively lower and thus they are more feasible.

RI-MDS: Multidimensional Scaling Iterative Localization Algorithm Using RSSI in Wireless Sensor Networks

To improve the feasibility and the convenience of localization methods for wireless sensor networks, a localization algorithm RI-MDS (RSSI-based Iterative-Multidimensional Scaling) is proposed. The RI-MDS method is centralized, and mainly focuses on improving localization accuracy. It collects RSSI vectors as ranging basis, and combines the metric-MDS method and the nonmetric MDS method to accomplish the relative localization. Then it uses the maximum likelihood method in affine transformation to transform the relative coordinates to absolute ones. Our method has no need for additional equipment on the WSN nodes. Simulation and field experiments show that the average localization error and the localization error ratio of the RI-MDS method is relatively lower, thus it is more feasible.

A MAC Protocol for Data Gathering in Linear Wireless Sensor Network Based on Selective Relay Nodes

Medium access control (MAC) protocol is very important for energy efficiency in WSN. Different from mesh WSN, linear WSN has specific features of long and narrow. An energy efficient MAC protocol is proposed for data gathering in linear WSN in this paper. In this protocol, the energy consumption factor and residual energy balance factor are defined and combined together to form a comprehensive energy consumption impact factor. In order to enhance the performance, specific nodes with small energy consumption impact factor are chosen as relay nodes when a source node transmits data to the sink. A gradient schedule mechanism is used to schedule the sleep/wakeup states of nodes in each data collection cycle. Simulation experiments are conducted and the results show that SLDMAC provides better energy efficiency and long lifetime than the other two protocols with acceptable delay.