Node localization algorithm of wireless sensor networks with mobile beacon node

When maximum movement distance of beacon node is limited, in order to improve the localization accuracy of sensor nodes, node localization algorithm of wireless sensor networks with mobile beacon node (NLA_MB) is proposed. NLA_MB algorithm divides the movement area of beacon node into some hexagonal grids, and establishes optimization model of node localization errors according to the movement path constraint, movement distance constraint and other constraints of beacon node. Beacon node uses heuristic method to solve the model approximately based on virtual force theory and location information of guide sensor nodes, and obtains a moving path which is suitable for the current node distribution. According to location information of beacon node or anchor sensor nodes, sensor nodes use maximum likelihood estimation algorithm to calculate their own location coordinates. Simulation results show that NLA_MB algorithm is suitable for the distribution scenarios of sensor nodes, such as full coverage distribution, L-type distribution, Tian-type distribution and U-type distribution. It can increase the number of sojourn locations of beacon node and average number of anchor points of sensor nodes, and reduce average localization error of sensor nodes. Under certain conditions, NLA_MB algorithm outperforms DOUBLE_SCAN, ZSCAN, MLE, RSCAN and DBMS algorithms.

[1]  Jiming Chen,et al.  Data gathering optimization by dynamic sensing and routing in rechargeable sensor networks , 2013, 2013 IEEE International Conference on Sensing, Communications and Networking (SECON).

[2]  Chih-Yung Chang,et al.  Anchor-Guiding Mechanism for Beacon-Assisted Localization in Wireless Sensor Networks , 2012, IEEE Sensors Journal.

[3]  David Simplot-Ryl,et al.  Dynamic Beacon Mobility Scheduling for Sensor Localization , 2012, IEEE Transactions on Parallel and Distributed Systems.

[4]  Yongzhao Zhan,et al.  Maximum Neighborhood Margin Discriminant Projection for Classification , 2014, TheScientificWorldJournal.

[5]  Peng Gao,et al.  A Location Predicting Method for Indoor Mobile Target Localization in Wireless Sensor Networks , 2013, Int. J. Distributed Sens. Networks.

[6]  Grid-Based Localization Mechanism with Mobile Reference Node in Wireless Sensor Networks , 2014 .

[7]  Wen-an Zhang,et al.  Hierarchical Fusion Estimation for Clustered Asynchronous Sensor Networks , 2016, IEEE Transactions on Automatic Control.

[8]  Chai Zhi.  Sensor Redeployment Algorithm Based on Combined Virtual Forces in Three Dimensional Space , 2011 .

[9]  Gang Feng,et al.  Multi-rate distributed fusion estimation for sensor networks with packet losses , 2012, Autom..

[10]  Li-Ling Hung,et al.  Temporal coverage mechanism for distinct quality of monitoring in wireless mobile sensor networks , 2014, Ad Hoc Networks.

[11]  Hadi Moradi,et al.  The modified Hilbert path for mobile-beacon-based localization in wireless sensor networks , 2014 .

[12]  Gergely V. Záruba,et al.  Static Path Planning for Mobile Beacons to Localize Sensor Networks , 2007, Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerComW'07).

[13]  Eryk Dutkiewicz,et al.  Superior Path Planning Mechanism for Mobile Beacon-Assisted Localization in Wireless Sensor Networks , 2014, IEEE Sensors Journal.

[14]  Guangjie Han,et al.  LPTA: Location Predictive and Time Adaptive Data Gathering Scheme with Mobile Sink for Wireless Sensor Networks , 2014, TheScientificWorldJournal.

[15]  Youxian Sun,et al.  Guaranteed Performance Control of DFIG Variable-Speed Wind Turbines , 2016, IEEE Transactions on Control Systems Technology.

[16]  Xiaoyu Wang,et al.  Distributed Load Sharing of an Inverter-Based Microgrid With Reduced Communication , 2018, IEEE Transactions on Smart Grid.

[17]  H. Jin Kim,et al.  Target Localization in Wireless Sensor Networks Using Online Semi-Supervised Support Vector Regression , 2015, Sensors.

[18]  Yourong Chen,et al.  Lifetime Optimization Algorithm with Mobile Sink Nodes for Wireless Sensor Networks Based on Location Information , 2015, Int. J. Distributed Sens. Networks.

[19]  Ling Shi,et al.  Optimal Denial-of-Service Attack Scheduling With Energy Constraint , 2015, IEEE Transactions on Automatic Control.

[20]  Ling Shi,et al.  Optimal DoS Attack Scheduling in Wireless Networked Control System , 2016, IEEE Transactions on Control Systems Technology.

[21]  Takahiro Hara,et al.  Localization algorithms of Wireless Sensor Networks: a survey , 2011, Telecommunication Systems.

[22]  Fu Qin,et al.  Beacon Dynamic Movement Strategy in Node Localization for Wireless Sensor Networks , 2012 .

[23]  Xin Ling.  Optimized Localization Scheme for Mobile Wireless Sensor Networks Based on Monte Carlo Method , 2013 .

[24]  Jiming Chen,et al.  Utility-based asynchronous flow control algorithm for wireless sensor networks , 2010, IEEE Journal on Selected Areas in Communications.

[25]  Dongbing Gu,et al.  Localization in wireless sensor networks using a mobile anchor node , 2008, 2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[26]  Takahiro Hara,et al.  Path planning using a mobile anchor node based on trilateration in wireless sensor networks , 2013, Wirel. Commun. Mob. Comput..

[27]  Bing-Hong Liu,et al.  Message-Efficient Location Prediction for Mobile Objects in Wireless Sensor Networks Using a Maximum Likelihood Technique , 2011, IEEE Transactions on Computers.