Multi‐hop localization system for environmental monitoring in wireless sensor and actor networks

Location estimation of sensor nodes is an essential part of most applications for wireless sensor and actor networks. The ambiguous location information often makes the collected data useless in these applications. Environmental monitoring relies on an accurate position estimation to process or evaluate the collected data. In this paper, we present a novel and scalable approach for positioning of mobile sensor nodes with the goal of monitoring the Amazon river. The actors in the scenario are stationary and positioned at reachable spots on the land alongside the river whereas sensor nodes are thrown into the river to collect data such as water temperature, depth, and geographical features. The actors are not equipped with positioning adaptors, and they are only aware of their distances from the other actors. The sensor nodes collect data and forward it to the actors. While floating in the river, sensor nodes are often multiple hops away from the actors, which makes it challenging to apply traditional positioning techniques. Through extensive simulations, we show that the nodes can be efficiently positioned using a multi‐hop approach with local information exchange only. The introduced approach is also applied to a scenario, where monkey swarm monitoring is simulated, to test the generalizability of the algorithm. Copyright © 2011 John Wiley & Sons, Ltd.

[1]  Qiang Cheng,et al.  Landscape-3D; A Robust Localization Scheme for Sensor Networks over Complex 3D Terrains , 2006, Proceedings. 2006 31st IEEE Conference on Local Computer Networks.

[2]  Albert Y. Zomaya,et al.  A genetic algorithm for finding optimal location area configurations for mobility management , 2005, The IEEE Conference on Local Computer Networks 30th Anniversary (LCN'05)l.

[3]  Haiyun Luo,et al.  TTDD: Two-Tier Data Dissemination in Large-Scale Wireless Sensor Networks , 2005, Wirel. Networks.

[4]  Xiaoli Li,et al.  Error analysis of quantised RSSI based sensor network localisation , 2010, Int. J. Wirel. Mob. Comput..

[5]  Matthias R. Brust,et al.  Adaptive multi-hop clustering in mobile networks , 2007, Mobility '07.

[6]  Richard P. Martin,et al.  A multi-hypothesis particle filter for indoor dynamic localization , 2009, 2009 IEEE 34th Conference on Local Computer Networks.

[7]  B. R. Badrinath,et al.  Ad hoc positioning system (APS) , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[8]  Azzedine Boukerche,et al.  A Novel Location-Free Greedy Forward Algorithm for Wireless Sensor Networks , 2008, 2008 IEEE International Conference on Communications.

[9]  Sajal K. Das,et al.  WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks , 2002, Cluster Computing.

[10]  R.L. Moses,et al.  Locating the nodes: cooperative localization in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[11]  Richard P. Martin,et al.  Using a-priori information to improve the accuracy of indoor dynamic localization , 2009, MSWiM '09.

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

[13]  J. Mcneff The global positioning system , 2002 .

[14]  Azzedine Boukerche,et al.  An Efficient Directed Localization Recursion Protocol for Wireless Sensor Networks , 2009, IEEE Transactions on Computers.

[15]  Richard P. Martin,et al.  Bayesian localization in wireless networks using angle of arrival , 2005, SenSys '05.

[16]  Radhika Nagpal,et al.  Organizing a Global Coordinate System from Local Information on an Ad Hoc Sensor Network , 2003, IPSN.

[17]  Mani Srivastava,et al.  Dynamic Fine-Grained Localization in Ad-Hoc Wireless Sensor Networks , 2001 .

[18]  Brian D. O. Anderson,et al.  Graphical properties of easily localizable sensor networks , 2009, Wirel. Networks.

[19]  Deborah Estrin,et al.  SCALE: A tool for Simple Connectivity Assessment in Lossy Environments , 2003 .

[20]  Brendan O'Flynn,et al.  A demonstration of wireless sensing for long term monitoring of water quality , 2009, 2009 IEEE 34th Conference on Local Computer Networks.

[21]  Richard P. Martin,et al.  Localization for indoor wireless networks using minimum intersection areas of iso-RSS lines , 2007, 32nd IEEE Conference on Local Computer Networks (LCN 2007).

[22]  Ian F. Akyildiz,et al.  Wireless sensor and actor networks: research challenges , 2004, Ad Hoc Networks.

[23]  Jan M. Rabaey,et al.  Robust Positioning Algorithms for Distributed Ad-Hoc Wireless Sensor Networks , 2002, USENIX Annual Technical Conference, General Track.

[24]  Mani B. Srivastava,et al.  Dynamic fine-grained localization in Ad-Hoc networks of sensors , 2001, MobiCom '01.

[25]  Richard P. Martin,et al.  Restarting Particle Filters: An Approach to Improve the Performance of Dynamic Indoor Localization , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[26]  Brian D. O. Anderson,et al.  Sequential Localization of Sensor Networks , 2009, SIAM J. Control. Optim..

[27]  I.A. Getting,et al.  Perspective/navigation-The Global Positioning System , 1993, IEEE Spectrum.

[28]  Pieter H. Hartel,et al.  Energy-Efficient Cluster-Based Service Discovery in Wireless Sensor Networks , 2006, Proceedings. 2006 31st IEEE Conference on Local Computer Networks.

[29]  B. R. Badrinath,et al.  DV Based Positioning in Ad Hoc Networks , 2003, Telecommun. Syst..

[30]  Azzedine Boukerche,et al.  HPEQ A Hierarchical Periodic, Event-driven and Query-based Wireless Sensor Network Protocol , 2005, The IEEE Conference on Local Computer Networks 30th Anniversary (LCN'05)l.