editorial location-related challenges and strategies in...

EditorialLocation-Related Challenges and Strategies inWireless Sensor Networks

Dingyi Fang,1 Chase Q. Wu,2 Jie Wang,3 Lin Cai,4 and Xiaohong Jiang5

1School of Information Science and Technology, Northwest University, Xi’an 710127, China2Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA3School of Communication and Information Technology, Dalian University of Technology, Dalian 116024, China4Department of Electrical & Computer Engineering, University of Victoria, Victoria, BC, Canada V8W 3P65Computer Communications Networks, Future University Hakodate, Hakodate, Hokkaido 041-8655, Japan

Correspondence should be addressed to Dingyi Fang; [email protected]

Received 6 July 2015; Accepted 6 July 2015

Copyright © 2015 Dingyi Fang et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

With the data gathered by distributed sensor nodes, we areable to obtain an accurate view of the field being monitoredfor various purposes such as environmental surveillance,object detection, and target tracking. Among all the sensorparameters in wireless sensor networks (WSNs), locationinformation is of crucial importance as it affects almost everystage of the application including node deployment, datacollection, information fusion, and decision making. How-ever, determining and utilizing location information facesignificant challenges such as time synchronization issues,physical layer measurement errors, computation constraints,and lack of GPS reference especially on low-cost sensor nodesthat are now made possible by the recent advances in themicroelectromechanical systems (MEMS) technology.Mean-while, modern sensor network applications pose increas-ingly complex and stringent performance requirements onlocalization in terms of scalability, robustness, and accuracy.Moreover, many new location-related issues such as securityand privacy in WSNs are rapidly emerging and must becarefully considered and addressed.

Given the significance and timeliness of the topic, thisspecial issue has attracted a great deal of attention fromresearchers around the world, and every accepted paper wentthrough a thorough review process by the invited reviewersand the guest editors. We compile this special issue with thelatest research progress and potential solutions to variouslocation-related services.

Some of the papers propose effective solutions to local-ization. Z. Tang et al. in their paper entitled “CTLL: ACell-Based Transfer Learning Method for Localization inLarge Scale Wireless Sensor Networks” consider a new wayfor localization, which is robust to the variances of nodedensity and SNR. CTLL combines sample transfer learningand a support vector regression model to obtain a betterperformance of localization. J. Trogh et al. in their paperentitled “Advanced Real-Time Indoor Tracking Based on theViterbi Algorithm and Semantic Data” develop a real-timeindoor tracking system based on the Viterbi algorithm andsemantic data to improve the accuracy. W. Wang et al. intheir paper entitled “A Grid-Based Linear Least Squares Self-Localization Algorithm in Wireless Sensor Network” study anovel grid-based linear least squares (LLS) self-localizationalgorithm for a nonuniform network. Furthermore, by takinginto consideration the quasi-uniform distribution of anchorsin the area, the authors select suitable anchors to assist inthe localization. Z. Xiahou and X. Zhang in their paperentitled “Adaptive Localization in Wireless Sensor Networkthrough Bayesian Compressive Sensing” estimate the loca-tion of targets in WSNs within the Bayesian compressivesensing (BCS) framework and provide adaptive iteration BCSlocalization (AIBCSL) algorithm, which is based on BCS andadaptively chooses measurement sensors according to theenvironment only with an initial value. Q. Wu et al. in theirpaper entitled “An All-Time-Domain Moving Object Data

Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2015, Article ID 571796, 3 pageshttp://dx.doi.org/10.1155/2015/571796

2 International Journal of Distributed Sensor Networks

Model, Location Updating Strategy, and Position Estimation”establish an object-oriented all-time-domain data model formoving objects, propose a new dynamic threshold locationupdating strategy based on the all-time-domain data model,and present several different all-time-domain position esti-mation methods. J. Liu and Q. Wang in their paper entitled“Position Prediction Based Frequency Control of Beacons inVehicular Ad Hoc Networks” propose a position predictionbased beacon approach to reduce beacon frequency anddecrease bandwidth consumption. S. Lee et al. in their paperentitled “Kalman Filter-Based Indoor Position Tracking withSelf-Calibration for RSS Variation Mitigation” investigate theindoor position tracking problem under the variation ofreceived signal strength (RSS) characteristic from the changesof device statuses and environmental factors. C. Miao et al.in their paper entitled “RI-MDS: Multidimensional ScalingIterative Localization Algorithm Using RSSI in WirelessSensor Networks” propose localization algorithm RI-MDS(RSSI-based Iterative-Multidimensional Scaling) to improvethe feasibility and the convenience of localization methodsfor wireless sensor networks. B. Zhang et al. in their paperentitled “A Hybrid Localization Approach in 3D WirelessSensor Network” develop a novel hybrid localization schemewhich utilizes the range-based attribute RSSI and the range-free attribute hop size to achieve accurate yet low-cost 3Dlocalization. Z. Sun et al. in their paper entitled “LocalizationAlgorithm in Wireless Sensor Networks Based on Multiob-jective Particle Swarm Optimization” propose a multiobjec-tive particle swarmoptimization based localization algorithmto solve the multiobjective optimization localization issuesin WSNs. Y. Chen et al. in their paper entitled “A FuzzySimilarity Elimination Algorithm for Indoor FingerprintPositioning” propose a K-Means+ clustering algorithm toachieve fine-grained fingerprint positioning, design a lin-ear sequence matching algorithm to improve the outlierspositioning, and reduce the impact of fuzzy similarity. S.Kim and J.-W. Chong in their paper entitled “An EfficientTDOA-Based Localization Algorithm without Synchroniza-tion between Base Stations” propose an efficient localizationalgorithm by utilizing the time difference of arrival (TDOA)without synchronization between base stations. X. Yin etal. in their paper entitled “Localizing Wireless Sensors withDiverse Granularities in Wireless Sensor Networks” proposea novel on-demand node localization technology, NLMR,with diverse granularities based on a multiresolution model.

Some of the papers deal with privacy preserving forlocalization. N. Nguyen et al. in their paper entitled “URALP:Unreachable Region Aware Location Privacy against Max-imum Movement Boundary Attack” propose an algorithmto prevent the adversary from effectively compromising theuser’s location privacy while achieving k-anonymity require-ments as well as minimum acceptable cloaked-region size.D. Song et al. in their paper entitled “A Privacy-PreservingContinuous LocationMonitoring System for Location-BasedServices” propose a cloaking system model called anonymityof motion vectors (AMV) that provides anonymity for spatialqueries.

Some of the papers develop potential solutions tolocation-based route finding and planning. Y. Chen et al. in

their paper entitled “Lifetime Optimization Algorithm withMobile Sink Nodes for Wireless Sensor Networks Based onLocation Information” propose a lifetime optimization algo-rithm with mobile sink nodes for wireless sensor networks(LOA MSN). In LOA MSN,movement path constraints, flowconstraint, energy consumption constraint, link transmissionconstraint, and other constraints are analyzed based onlocation information. P. Duan et al. in their paper entitled “ACross Layer Video Transmission Scheme Combining Geo-graphic Routing and Short-Length Luby Transform Codes”combine geographic routing in the network layer and short-length Luby Transform (LT) codes in the transport layer,design a routing metric for geographic routing, and proposea cross layer transmission scheme, which adaptively adjustspayload length to encapsulate short-length LT encoded sym-bols and selects routes based on the new routing metric.X. Niu et al. in their paper entitled “An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City”propose an innovative online-traffic-prediction based routefinding mechanism, O-Sense, which utilizes large-scale taxiGPS traces and environmental information.

Some of the papers tackle other important issues relatedto localization. X. Liu et al. in their paper entitled “RobustMonitor Assignment with Minimum Cost for Sensor Net-work Tomography” propose a robust monitor assignmentalgorithm to assign monitors in large-scale sensor networkswith dynamically changing topology. S. Kim and J.-W. Chongin their paper entitled “Chirp Spread Spectrum TransceiverDesign and Implementation for Real Time Locating Sys-tem” design and implement a chirp spread spectrum (CSS)transceiver architecture for IEEE 802.15.4a. J. Yang et al.in their paper entitled “A Group Mining Method for BigData on Distributed Vehicle Trajectories in WAN” pro-pose a distributed parallel clustering method, MCR-ACA,by integrating the Ant Colony Algorithm with the Map-Combine-Reduce computing framework for mining groupswith the same or similar features from big data on vehicletrajectories stored in wide area networks. J. Luo et al. intheir paper entitled “Location-Based Data Aggregation in6LoWPAN” propose a novel location-based data aggregationmodel, LDAA, which aggregates data from the network layeraccording to the MAC layer queuing delay. X. Jiao et al.in their paper entitled “On Minimum-Latency Broadcastin Multichannel Duty-Cycled Wireless Sensor Networks”investigate the MLB problem in multichannel duty-cycledWSNs, prove that MLBCD problem is NP-hard, and proposea new concept of active interference graph (AIG). Y. Xinget al. in their paper entitled “Time Synchronization forWireless Sensor Networks using Adaptive Linear Predic-tion” present an Adaptive Linear Prediction Synchronization(ALPS) scheme for WSNs by applying linear prediction onsynchronization errors and adaptively adjusting predictioncoefficients.

Acknowledgments

We would like to thank the authors for their great contribu-tions to this special issue.We are particularly thankful to all ofthe reviewers for their valuable comments, suggestions, and

International Journal of Distributed Sensor Networks 3

timely responses. Finally, we hope that the papers publishedin this special issue would be helpful to other researchers witha common interest in these location-related topics.

Dingyi FangChase Q. Wu

Jie WangLin Cai

Xiaohong Jiang

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttp://www.hindawi.com Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014


Active and Passive Electronic Components

Control Scienceand Engineering

Journal of



RotatingMachinery


Hindawi Publishing Corporation http://www.hindawi.com

Journal ofEngineeringVolume 2014

Submit your manuscripts athttp://www.hindawi.com

VLSI Design



Shock and Vibration


Civil EngineeringAdvances in

Acoustics and VibrationAdvances in



Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation http://www.hindawi.com

Volume 2014

The Scientific World JournalHindawi Publishing Corporation http://www.hindawi.com Volume 2014

SensorsJournal of


Modelling & Simulation in EngineeringHindawi Publishing Corporation http://www.hindawi.com Volume 2014


Chemical EngineeringInternational Journal of Antennas and

Propagation




Navigation and Observation



DistributedSensor Networks


editorial location-related challenges and strategies in...

Documents