Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in WSNs. The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.

[1]  Pramod K. Varshney,et al.  QoS Support in Wireless Sensor Networks: A Survey , 2004, International Conference on Wireless Networks.

[2]  Chenyang Lu,et al.  A component-based architecture for power-efficient media access control in wireless sensor networks , 2007, SenSys '07.

[3]  Kai Li,et al.  A directionality based location discovery scheme for wireless sensor networks , 2002, WSNA '02.

[4]  D.M. Mount,et al.  An Efficient k-Means Clustering Algorithm: Analysis and Implementation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Michele Zorzi,et al.  A Bayesian analysis of Compressive Sensing data recovery in Wireless Sensor Networks , 2009, 2009 International Conference on Ultra Modern Telecommunications & Workshops.

[6]  Li-Chen Fu,et al.  Robust Location-Aware Activity Recognition Using Wireless Sensor Network in an Attentive Home , 2009, IEEE Transactions on Automation Science and Engineering.

[7]  Jonathan Goldstein,et al.  When Is ''Nearest Neighbor'' Meaningful? , 1999, ICDT.

[8]  Wang-Chien Lee,et al.  Energy efficient processing of K nearest neighbor queries in location-aware sensor networks , 2005, The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services.

[9]  Wendi B. Heinzelman,et al.  Application-specific protocol architectures for wireless networks , 2000 .

[10]  David A. Landgrebe,et al.  A survey of decision tree classifier methodology , 1991, IEEE Trans. Syst. Man Cybern..

[11]  Yong Wang,et al.  Predicting link quality using supervised learning in wireless sensor networks , 2007, MOCO.

[12]  Vedat Coskun,et al.  Wireless sensor networks for underwater survelliance systems , 2006, Ad Hoc Networks.

[13]  Luca Benini,et al.  Activity Recognition from On-Body Sensors: Accuracy-Power Trade-Off by Dynamic Sensor Selection , 2008, EWSN.

[14]  Ganesh K. Venayagamoorthy,et al.  Computational Intelligence in Wireless Sensor Networks: A Survey , 2011, IEEE Communications Surveys & Tutorials.

[15]  E. Board.  Journal of Network and Systems Management , 2005, Journal of Network and Systems Management.

[16]  Salim Hariri,et al.  Analyzing Attacks in Wireless Ad Hoc Network with Self-Organizing Maps , 2007, Fifth Annual Conference on Communication Networks and Services Research (CNSR '07).

[17]  Yu Sheng Chen,et al.  Intrusion Detection System Based on Immune Algorithm and Support Vector Machine in Wireless Sensor Network , 2010, ISIA.

[18]  Kin K. Leung,et al.  MAC Essentials for Wireless Sensor Networks , 2010, IEEE Communications Surveys & Tutorials.

[19]  Chenyang Lu,et al.  Self-Adapting MAC Layer for Wireless Sensor Networks , 2013, 2013 IEEE 34th Real-Time Systems Symposium.

[20]  Antonio Puliafito,et al.  Self Organizing Maps for Synchronization in Wireless Sensor Networks , 2008, 2008 New Technologies, Mobility and Security.

[21]  Jonathan Timmis,et al.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[22]  Er Meng Joo,et al.  A survey of machine learning in Wireless Sensor netoworks From networking and application perspectives , 2007, 2007 6th International Conference on Information, Communications & Signal Processing.

[23]  Sanjeev R. Kulkarni,et al.  Learning Pattern Classification - A Survey , 1998, IEEE Trans. Inf. Theory.

[24]  Dan Feldman,et al.  Turning big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering , 2013, SODA.

[25]  Sudipto Guha,et al.  CURE: an efficient clustering algorithm for large databases , 1998, SIGMOD '98.

[26]  T. Weingart,et al.  MultiMAC - an adaptive MAC framework for dynamic radio networking , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[27]  Mohamed A. Elgamel,et al.  A Lightweight Collaborative Fault Tolerant Target Localization System for Wireless Sensor Networks , 2009, IEEE Transactions on Mobile Computing.

[28]  Chanchal Kumar Roy,et al.  A methodology to optimize query in wireless sensor networks using historical data , 2011, J. Ambient Intell. Humaniz. Comput..

[29]  Victor C. M. Leung,et al.  A novel cooperative communication protocol for QoS provisioning in wireless sensor networks , 2009, 2009 5th International Conference on Testbeds and Research Infrastructures for the Development of Networks & Communities and Workshops.

[30]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[31]  Dimitrios Gunopulos,et al.  Online Information Compression in Sensor Networks , 2006, 2006 IEEE International Conference on Communications.

[32]  Yifeng Zhu,et al.  Localization using neural networks in wireless sensor networks , 2008, MOBILWARE.

[33]  Alex H. B. Duffy,et al.  The "What" and "How" of Learning in Design , 1997, IEEE Expert.

[34]  David B. Lowe,et al.  Dynamic Path Determination of Mobile Beacons Employing Reinforcement Learning for Wireless Sensor Localization , 2012, 2012 26th International Conference on Advanced Information Networking and Applications Workshops.

[35]  Prem Prakash Jayaraman,et al.  Intelligent Processing of K-Nearest Neighbors Queries Using Mobile Data Collectors in a Location Aware 3D Wireless Sensor Network , 2010, International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems.

[36]  Rastko R. Selmic,et al.  Wireless Sensor Network Modeling Using Modified Recurrent Neural Networks: Application to Fault Detection , 2008, IEEE Transactions on Instrumentation and Measurement.

[37]  Muriel Médard,et al.  Compressive sensing over networks , 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[38]  Y.A. Sekercioglu,et al.  Detecting Selective Forwarding Attacks in Wireless Sensor Networks using Support Vector Machines , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[39]  Sergio Valcarcel Macua,et al.  Consensus-based distributed principal component analysis in wireless sensor networks , 2010, 2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[40]  Krishna M. Sivalingam,et al.  Reinforcement Learning Based Geographic Routing Protocol for UWB Wireless Sensor Network , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[41]  Omer Gurewitz,et al.  RI-MAC: a receiver-initiated asynchronous duty cycle MAC protocol for dynamic traffic loads in wireless sensor networks , 2008, SenSys '08.

[42]  Duc A. Tran,et al.  Localization In Wireless Sensor Networks Based on Support Vector Machines , 2008, IEEE Transactions on Parallel and Distributed Systems.

[43]  JAMAL N. AL-KARAKI,et al.  Routing techniques in wireless sensor networks: a survey , 2004, IEEE Wireless Communications.

[44]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[45]  Nando de Freitas,et al.  Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.

[46]  Krste Asanovic,et al.  Energy-aware lossless data compression , 2006, TOCS.

[47]  George S. Oreku,et al.  Quality of Service in Wireless Sensor Networks , 2014 .

[48]  H. Søgaard,et al.  ZigBee-based wireless sensor networks for classifying the behaviour of a herd of animals using classification trees , 2008 .

[49]  Koby Crammer,et al.  Adaptive regularization of weight vectors , 2009, Machine Learning.

[50]  C. Guestrin,et al.  Distributed regression: an efficient framework for modeling sensor network data , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[51]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[52]  Erkki Mäkinen,et al.  A Neural Network Model to Minimize the Connected Dominating Set for Self-Configuration of Wireless Sensor Networks , 2009, IEEE Transactions on Neural Networks.

[53]  S. Sitharama Iyengar,et al.  Distributed Bayesian algorithms for fault-tolerant event region detection in wireless sensor networks , 2004, IEEE Transactions on Computers.

[54]  Steven C. H. Hoi,et al.  Exact Soft Confidence-Weighted Learning , 2012, ICML.

[55]  Dongbing Gu,et al.  Spatial Gaussian Process Regression With Mobile Sensor Networks , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[56]  Deborah Estrin,et al.  The impact of data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems Workshops.

[57]  Kuan-Chieh Wang,et al.  QoS-Aware Power Management for Energy Harvesting Wireless Sensor Network Utilizing Reinforcement Learning , 2009, 2009 International Conference on Computational Science and Engineering.

[58]  A. Snow,et al.  Assessing dependability of wireless networks using neural networks , 2005, MILCOM 2005 - 2005 IEEE Military Communications Conference.

[59]  David E. Culler,et al.  Taming the underlying challenges of reliable multihop routing in sensor networks , 2003, SenSys '03.

[60]  Deborah Estrin,et al.  An energy-efficient MAC protocol for wireless sensor networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[61]  Shoji Tatsumi,et al.  Q-MAP: a novel multicast routing method in wireless ad hoc networks with multiagent reinforcement learning , 2002, 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering. TENCOM '02. Proceedings..

[62]  Sajal K. Das,et al.  A survey on sensor localization , 2010 .

[63]  D. Janakiram,et al.  Outlier Detection in Wireless Sensor Networks using Bayesian Belief Networks , 2006, 2006 1st International Conference on Communication Systems Software & Middleware.

[64]  V. Srinivasan,et al.  Achieving Coverage through Distributed Reinforcement Learning in Wireless Sensor Networks , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[65]  O.A. Postolache,et al.  Smart Sensors Network for Air Quality Monitoring Applications , 2005, IEEE Transactions on Instrumentation and Measurement.

[66]  Yu-Chee Tseng,et al.  iMouse: An Integrated Mobile Surveillance and Wireless Sensor System , 2007, Computer.

[67]  Yonina C. Eldar,et al.  Structured Compressed Sensing: From Theory to Applications , 2011, IEEE Transactions on Signal Processing.

[68]  G. Giorgetti,et al.  Wireless Localization Using Self-Organizing Maps , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[69]  Matthias W. Seeger,et al.  Gaussian Processes For Machine Learning , 2004, Int. J. Neural Syst..

[70]  Victoria J. Hodge,et al.  A Survey of Outlier Detection Methodologies , 2004, Artificial Intelligence Review.

[71]  Wendi B. Heinzelman,et al.  Prolonging the lifetime of wireless sensor networks via unequal clustering , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[72]  Victor C. M. Leung,et al.  MRL-CC: a novel cooperative communication protocol for QoS provisioning in wireless sensor networks , 2010, Int. J. Sens. Networks.

[73]  V. Ramachandran,et al.  Distributed multitarget classification in wireless sensor networks , 2005, IEEE Journal on Selected Areas in Communications.

[74]  A. Forster,et al.  Machine Learning Techniques Applied to Wireless Ad-Hoc Networks: Guide and Survey , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[75]  Man-Gon Park,et al.  Bayesian Statistical Modeling of System Energy Saving Effectiveness for MAC Protocols of Wireless Sensor Networks , 2010, Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing.

[76]  Winston K. G. Seah,et al.  A Survey of Techniques and Challenges in Underwater Localization , 2011 .

[77]  Soohan Kim,et al.  A soft computing approach to localization in wireless sensor networks , 2009, Expert Syst. Appl..

[78]  Gordon Lee,et al.  Distributed localization of wireless sensor networks using self-organizing maps , 2008, 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.

[79]  Peter Dayan,et al.  Technical Note: Q-Learning , 2004, Machine Learning.

[80]  Yoshua. Bengio,et al.  Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..

[81]  Ajith Abraham,et al.  Computational Intelligence: Foundations, Perspectives, and Recent Trends , 2010 .

[82]  Antonio Puliafito,et al.  Self Organizing Maps for Distributed Localization in Wireless Sensor Networks , 2007, 2007 12th IEEE Symposium on Computers and Communications.

[83]  G. C. Tiao,et al.  Bayesian inference in statistical analysis , 1973 .

[84]  H. Vincent Poor,et al.  Distributed learning in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[85]  A. Forstert,et al.  FROMS: Feedback Routing for Optimizing Multiple Sinks in WSN with Reinforcement Learning , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[86]  Jörg Widmer,et al.  Data Acquisition through Joint Compressive Sensing and Principal Component Analysis , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[87]  Ming-Shi Wang,et al.  Broadcast scheduling in wireless sensor networks using fuzzy Hopfield neural network , 2008, Expert Syst. Appl..

[88]  Feng Xia,et al.  From machine-to-machine communications towards cyber-physical systems , 2013, Comput. Sci. Inf. Syst..

[89]  R. Michael Buehrer,et al.  Ultra-Wideband Wireless Systems , 2005 .

[90]  J. Cid-Sueiro,et al.  Q-Probabilistic Routing in Wireless Sensor Networks , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[91]  Amy L. Murphy,et al.  CLIQUE: Role-Free Clustering with Q-Learning for Wireless Sensor Networks , 2009, 2009 29th IEEE International Conference on Distributed Computing Systems.

[92]  Geoffrey E. Hinton,et al.  Reducing the Dimensionality of Data with Neural Networks , 2006, Science.

[93]  Anna Förster,et al.  Machine Learning across the WSN Layers , 2011 .

[94]  Herbert A. Simon,et al.  Applications of machine learning and rule induction , 1995, CACM.

[95]  M. Degroot.  Reaching a Consensus , 1974 .

[96]  Pingzhi Fan,et al.  Comments on "Distributed Bayesian Algorithms for Fault-Tolerant Event Region Detection in Wireless Sensor Networks' , 2005, IEEE Trans. Computers.

[97]  Xiaoqiao Meng,et al.  Real-time forest fire detection with wireless sensor networks , 2005, Proceedings. 2005 International Conference on Wireless Communications, Networking and Mobile Computing, 2005..

[98]  João B. Martins,et al.  An approach to localization scheme of wireless sensor networks based on artificial neural networks and Genetic Algorithms , 2012, 10th IEEE International NEWCAS Conference.

[99]  Yu Hen Hu,et al.  Detection, classification, and tracking of targets , 2002, IEEE Signal Process. Mag..

[100]  Qi Han,et al.  Journal of Network and Systems Management ( c ○ 2007) DOI: 10.1007/s10922-007-9062-0 A Survey of Fault Management in Wireless Sensor Networks , 2022 .

[101]  Kay Römer,et al.  The design space of wireless sensor networks , 2004, IEEE Wireless Communications.

[102]  G. Ahmed,et al.  Cluster head selection using decision trees for Wireless Sensor Networks , 2008, 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[103]  SangHak Lee,et al.  Data Aggregation for Wireless Sensor Networks Using Self-organizing Map , 2004, AIS.

[104]  Bin Yang,et al.  Area Localization Algorithm for Mobile Nodes in Wireless Sensor Networks Based on Support Vector Machines , 2007, MSN.

[105]  Zhenzhen Liu,et al.  RL-MAC: a reinforcement learning based MAC protocol for wireless sensor networks , 2006, Int. J. Sens. Networks.

[106]  Emre Ertin,et al.  Gaussian Process Models for Censored Sensor Readings , 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.

[107]  P. Levis,et al.  BoX-MACs : Exploiting Physical and Link Layer Boundaries in Low-Power Networking , 2007 .

[108]  Tian Zhang,et al.  BIRCH: an efficient data clustering method for very large databases , 1996, SIGMOD '96.

[109]  Catherine Rosenberg,et al.  Does Compressed Sensing Improve the Throughput of Wireless Sensor Networks? , 2010, 2010 IEEE International Conference on Communications.

[110]  Hamid R. Rabiee,et al.  Reducing the data transmission in Wireless Sensor Networks using the Principal Component Analysis , 2010, 2010 Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[111]  Yandan Lin,et al.  A wireless sensor network based on the novel concept of an I-matrix to achieve high-precision lighting control , 2013 .

[112]  Abdelhamid Mellouk,et al.  A QoS Scheduler Packets for Wireless Sensor Networks , 2007, 2007 IEEE/ACS International Conference on Computer Systems and Applications.

[113]  Zahra Taghikhaki,et al.  Distributed Event Detection in Wireless Sensor Networks for Disaster Management , 2010, 2010 International Conference on Intelligent Networking and Collaborative Systems.

[114]  Ian T. Jolliffe,et al.  Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.

[115]  Jieping Ye,et al.  Online learning by ellipsoid method , 2009, ICML '09.

[116]  Mark R. Morelande,et al.  Bayesian node localisation in wireless sensor networks , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[117]  Achim G. Hoffmann.  General Limitations on Machine Learning , 1990, ECAI.

[118]  Ganesh K. Venayagamoorthy,et al.  Neural network based secure media access control protocol for wireless sensor networks , 2009, 2009 International Joint Conference on Neural Networks.

[119]  Andreas Christmann,et al.  Support vector machines , 2008, Data Mining and Knowledge Discovery Handbook.

[120]  David E. Culler,et al.  An architecture for energy management in wireless sensor networks , 2007, SIGBED.

[121]  Alexander J. Smola,et al.  Online learning with kernels , 2001, IEEE Transactions on Signal Processing.

[122]  Sarvapali D. Ramchurn,et al.  2008 International Conference on Information Processing in Sensor Networks Towards Real-Time Information Processing of Sensor Network Data using Computationally Efficient Multi-output Gaussian Processes , 2022 .

[123]  R. Nowak,et al.  Compressed Sensing for Networked Data , 2008, IEEE Signal Processing Magazine.

[124]  Seon-Ho Park,et al.  CHEF: Cluster Head Election mechanism using Fuzzy logic in Wireless Sensor Networks , 2008, 2008 10th International Conference on Advanced Communication Technology.

[125]  Marimuthu Palaniswami,et al.  Quarter Sphere Based Distributed Anomaly Detection in Wireless Sensor Networks , 2007, 2007 IEEE International Conference on Communications.

[126]  Carlos León,et al.  A new QoS routing algorithm based on self-organizing maps for wireless sensor networks , 2007, Telecommun. Syst..

[127]  H. Jin Kim,et al.  Target Localization Using Ensemble Support Vector Regression in Wireless Sensor Networks , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[128]  Zhang Yang,et al.  An online outlier detection technique for wireless sensor networks using unsupervised quarter-sphere support vector machine , 2008, 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[129]  N. Pissinou,et al.  A framework for trust-based cluster head election in wireless sensor networks , 2006, Second IEEE Workshop on Dependability and Security in Sensor Networks and Systems.

[130]  David Grace,et al.  ALOHA and Q-Learning based medium access control for Wireless Sensor Networks , 2012, 2012 International Symposium on Wireless Communication Systems (ISWCS).

[131]  Mohan Kumar,et al.  Distributed Independent Reinforcement Learning (DIRL) Approach to Resource Management in Wireless Sensor Networks , 2007, 2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems.

[132]  Ran Wolff,et al.  Noname manuscript No. (will be inserted by the editor) In-Network Outlier Detection in Wireless Sensor Networks , 2022 .

[133]  Nirvana Meratnia,et al.  Distributed online outlier detection in wireless sensor networks using ellipsoidal support vector machine , 2013, Ad Hoc Networks.

[134]  Ann Nowé,et al.  Decentralized Learning in Wireless Sensor Networks , 2009, ALA.

[135]  Andreas Krause,et al.  Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies , 2008, J. Mach. Learn. Res..

[136]  Shahram Latifi,et al.  A survey on data compression in wireless sensor networks , 2005, International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II.

[137]  Christian Musso,et al.  Improving Regularised Particle Filters , 2001, Sequential Monte Carlo Methods in Practice.

[138]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[139]  Nirvana Meratnia,et al.  Outlier Detection Techniques for Wireless Sensor Networks: A Survey , 2008, IEEE Communications Surveys & Tutorials.

[140]  Anis Koubaa,et al.  Radio link quality estimation in wireless sensor networks , 2012, ACM Trans. Sens. Networks.

[141]  Nicholas R. Jennings,et al.  Decentralized control of adaptive sampling in wireless sensor networks , 2009, TOSN.

[142]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[143]  Peter Dayan,et al.  Q-learning , 1992, Machine Learning.

[144]  Makoto Takizawa,et al.  A Survey on Clustering Algorithms for Wireless Sensor Networks , 2010, 2010 13th International Conference on Network-Based Information Systems.

[145]  Sudipto Guha,et al.  CURE: an efficient clustering algorithm for large databases , 1998, SIGMOD '98.

[146]  Taiwo Oladipupo Ayodele,et al.  Types of Machine Learning Algorithms , 2010 .

[147]  Koen Langendoen,et al.  An adaptive energy-efficient MAC protocol for wireless sensor networks , 2003, SenSys '03.

[148]  Alexander Zien,et al.  Semi-Supervised Learning , 2006 .

[149]  Anthony Widjaja,et al.  Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.

[150]  Yu-Jin Zhang,et al.  Nonnegative Matrix Factorization: A Comprehensive Review , 2013, IEEE Transactions on Knowledge and Data Engineering.

[151]  R. Lippmann,et al.  An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.

[152]  Pramod K. Varshney,et al.  Data-aggregation techniques in sensor networks: a survey , 2006, IEEE Communications Surveys & Tutorials.

[153]  Weisong Shi,et al.  Using Wireless Sensor Networks for Fire Rescue Applications: Requirements and Challenges , 2006, 2006 IEEE International Conference on Electro/Information Technology.