A Disaster Management-Oriented Path Planning for Mobile Anchor Node-Based Localization in Wireless Sensor Networks

The localization of sensor nodes is a significant issue in wireless sensor networks (WSNs) because many applications cannot provide services without geolocation data, especially during disaster management. In recent years, a promising unknown-nodes positioning method has been developed that localizes unknown nodes, employing a GPS-enabled mobile anchor node moving in the network, and broadcasting its location information periodically to assist localization. In contrast to most studies on path planning that assume infinite energy of the mobile anchor node, the anchor node in this study, consumes different amounts of energy during phases of startup, turning, and uniform motion considering the aftermath of disasters. To enable a trade-off between location accuracy and energy consumption, a path-planning algorithm combining a Localization algorithm with a Mobile Anchor node based on Trilateration (LMAT) and SCAN algorithm (SLMAT) is proposed. SLMAT ensures that each unknown node is covered by a regular triangle formed by beacons. Furthermore, the number of corners along the planned path is reduced to save the energy of the mobile anchor node. In addition, a series of experiments have been conducted to evaluate the performance of the SLMAT algorithm. Simulation results indicate that SLMAT outperforms SCAN, LMAT, HILBERT, and Z-curve in terms of localization accuracy and energy consumption.

[1]  Yunhao Liu,et al.  Perpendicular Intersection: Locating Wireless Sensors with Mobile Beacon , 2008, 2008 Real-Time Systems Symposium.

[2]  Xiao-Ping Zhang,et al.  Efficient Closed-Form Algorithms for AOA Based Self-Localization of Sensor Nodes Using Auxiliary Variables , 2014, IEEE Transactions on Signal Processing.

[3]  Radu Stoleru,et al.  Mobile Sensor Network Localization in Harsh Environments , 2010, DCOSS.

[4]  Zhang Hui,et al.  Cooperate localization of a Wireless Sensor Network (WSN) aided by a mobile robot , 2010, 2010 IEEE Safety Security and Rescue Robotics.

[5]  Emanuele Goldoni,et al.  Experimental analysis of RSSI-based indoor localization with IEEE 802.15.4 , 2010, 2010 European Wireless Conference (EW).

[6]  Joel J. P. C. Rodrigues,et al.  Real-time data management on wireless sensor networks: A survey , 2012, J. Netw. Comput. Appl..

[7]  Neeraj Jain,et al.  A novel distance estimation approach for 3D localization in wireless sensor network using multi dimensional scaling , 2014, Inf. Fusion.

[8]  Guangjie Han,et al.  Analysis of Energy-Efficient Connected Target Coverage Algorithms for Industrial Wireless Sensor Networks , 2017, IEEE Transactions on Industrial Informatics.

[9]  Shuigeng Zhou,et al.  Distributed Localization Using a Moving Beacon in Wireless Sensor Networks , 2008, IEEE Transactions on Parallel and Distributed Systems.

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

[11]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[12]  Joel J. P. C. Rodrigues,et al.  On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks , 2012, Sensors.

[13]  Sanjiv Tokekar,et al.  Mobility of sink using hexagon architecture in highly data centric Wireless Sensor Networks , 2012 .

[14]  Mohsen Guizani,et al.  Mobile anchor nodes path planning algorithms using network-density-based clustering in wireless sensor networks , 2017, J. Netw. Comput. Appl..

[15]  Dimitrios Koutsonikolas,et al.  Path planning of mobile landmarks for localization in wireless sensor networks , 2006, Comput. Commun..

[16]  Ismail Güvenç,et al.  A Survey on TOA Based Wireless Localization and NLOS Mitigation Techniques , 2009, IEEE Communications Surveys & Tutorials.

[17]  Guangjie Han,et al.  LDPA: a local data processing architecture in ambient assisted living communications , 2015, IEEE Communications Magazine.

[18]  Yan Zhang,et al.  Energy-Efficient Cross-Layer Protocol of Channel-Aware Geographic-Informed Forwarding in Wireless Sensor Networks , 2009, IEEE Transactions on Vehicular Technology.

[19]  Brian D. O. Anderson,et al.  Wireless sensor network localization techniques , 2007, Comput. Networks.

[20]  Lei Shu,et al.  Mobile big data fault-tolerant processing for ehealth networks , 2016, IEEE Network.

[21]  Marjan Moradi,et al.  A Reverse Localization Scheme for Underwater Acoustic Sensor Networks , 2012, Sensors.

[22]  Li Xiao,et al.  Using mobile beacons to locate sensors in obstructed environments , 2010, J. Parallel Distributed Comput..

[23]  Fang Hai-fen Research of energy consumption model of robot in coal mine post-disaster environment , 2015 .

[24]  Yunhao Liu,et al.  Location, Localization, and Localizability , 2010, Journal of Computer Science and Technology.

[25]  Chia-Ho Ou,et al.  Path Planning Algorithm for Mobile Anchor-Based Localization in Wireless Sensor Networks , 2013, IEEE Sensors Journal.

[26]  Hewijin Christine Jiau,et al.  Localization with mobile anchor points in wireless sensor networks , 2005, IEEE Transactions on Vehicular Technology.

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

[28]  Lingyang Song,et al.  Joint Optimization of Power, Packet Forwarding and Reliability in MIMO Wireless Sensor Networks , 2011, Mob. Networks Appl..

[29]  Yao-Hung Wu,et al.  An intelligent target localization in wireless sensor networks , 2014, 2014 International Conference on Intelligent Green Building and Smart Grid (IGBSG).

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

[31]  Li Liu,et al.  BRTCO: A Novel Boundary Recognition and Tracking Algorithm for Continuous Objects in Wireless Sensor Networks , 2018, IEEE Systems Journal.