Outlier detection based fault tolerant data aggregation for wireless sensor networks

Data aggregation protocols are essential for wireless sensor networks to prolong network lifetime by reducing energy consumption of sensor nodes. For mission-critical wireless sensor networks, however, not only the energy consumption of sensor nodes but also the correctness of the data aggregation results is critical. As wireless sensor networks are usually deployed in harsh and hostile environments, malfunctioning and/or compromised sensor nodes negatively affect the correctness of the data aggregation results. This paper presents a fault-tolerant data aggregation scheme that eliminates the false data sent by malfunctioning and/or compromised sensor nodes. To conserve energy while eliminating false data, an in-network outlier detection technique that is based on locality sensitive hashing scheme is used. The simulation results show that the proposed scheme is able to reduce the number of false data transmissions, thereby increasing the data aggregation accuracy. Moreover, it is also observed that the proposed scheme reduces the overall data transmission in the network. Copyright © 2012 John Wiley & Sons, Ltd.

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

[2]  Suat Ozdemir,et al.  Functional reputation based reliable data aggregation and transmission for wireless sensor networks , 2008 .

[3]  B. R. Badrinath,et al.  Cleaning and querying noisy sensors , 2003, WSNA '03.

[4]  Alex Delis,et al.  Another Outlier Bites the Dust: Computing Meaningful Aggregates in Sensor Networks , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[5]  Gustavo Alonso,et al.  Declarative Support for Sensor Data Cleaning , 2006, Pervasive.

[6]  M. S. Mohamed,et al.  Real Time Outlier Detection in Wireless Sensor Networks , 2011 .

[7]  Y. Zhang,et al.  – 20 Statistics-based outlier detection for wireless sensor networks , 2012 .

[8]  Vipnesh Jha,et al.  Outlier Detection Techniques and Cleaning of Data for Wireless Sensor Networks: A Survey , 2012 .

[9]  Moses Charikar,et al.  Similarity estimation techniques from rounding algorithms , 2002, STOC '02.

[10]  Sencun Zhu,et al.  Aggregation Protocol for Sensor Networks 2 , 2008 .

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

[12]  Douglas R. Stinson,et al.  On the Construction of Practical Key Predistribution Schemes for Distributed Sensor Networks Using Combinatorial Designs , 2008, TSEC.

[13]  David P. Williamson,et al.  Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming , 1995, JACM.

[14]  Alice M. Agogino,et al.  Fuzzy Validation and Fusion for Wireless Sensor Networks , 2004 .

[15]  Lei Chen,et al.  A Weighted Moving Average-based Approach for Cleaning Sensor Data , 2007, 27th International Conference on Distributed Computing Systems (ICDCS '07).

[16]  H. Cam,et al.  ESPDA: Energy-efficient and Secure Pattern-based Data Aggregation for wireless sensor networks , 2003, Proceedings of IEEE Sensors 2003 (IEEE Cat. No.03CH37498).

[17]  R. Suganya,et al.  Data Mining Concepts and Techniques , 2010 .

[18]  Sencun Zhu,et al.  SDAP: A Secure Hop-by-Hop Data Aggregation Protocol for Sensor Networks , 2008 .

[19]  Wang-Chien Lee,et al.  Using sensorranks for in-network detection of faulty readings in wireless sensor networks , 2007, MobiDE '07.

[20]  Dawn Xiaodong Song,et al.  SIA: secure information aggregation in sensor networks , 2003, SenSys '03.

[21]  Hasan Çam,et al.  Energy-efficient secure pattern based data aggregation for wireless sensor networks , 2006, Comput. Commun..

[22]  Christoph Heinz Bernhard Seeger Statistical Modeling of Sensor Data and its Application to Outlier Detection , 2006 .

[23]  Jyh-Ching Juang,et al.  Outlier-Detection-Based Indoor Localization System for Wireless Sensor Networks , 2012 .

[24]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[25]  Deborah Estrin,et al.  Impact of network density on data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems.

[26]  Lingxuan Hu,et al.  Secure aggregation for wireless networks , 2003, 2003 Symposium on Applications and the Internet Workshops, 2003. Proceedings..

[27]  Hans-Peter Kriegel,et al.  LOF: identifying density-based local outliers , 2000, SIGMOD '00.

[28]  Yunghsiang Sam Han,et al.  A witness-based approach for data fusion assurance in wireless sensor networks , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[29]  Yang Xiao,et al.  Secure data aggregation without persistent cryptographic operations in wireless sensor networks , 2007, Ad Hoc Networks.

[30]  David E. Culler,et al.  SPINS: security protocols for sensor networks , 2001, MobiCom '01.

[31]  Alexandr Andoni,et al.  Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions , 2006, 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06).

[32]  Bo Sheng,et al.  Outlier detection in sensor networks , 2007, MobiHoc '07.

[33]  Sasikanth Avancha,et al.  Security for Sensor Networks , 2004 .

[34]  Yi Jiang,et al.  A topology-aware hierarchical structured overlay network based on locality sensitive hashing scheme , 2007, UPGRADE '07.

[35]  Yang Xiao,et al.  Secure data aggregation in wireless sensor networks: A comprehensive overview , 2009, Comput. Networks.

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

[37]  Victor C. M. Leung,et al.  Directional Controlled Fusion in Wireless Sensor Networks , 2008, QShine '08.

[38]  Qiong Luo,et al.  Online Mining in Sensor Networks , 2004, NPC.

[39]  Arun Somani,et al.  Distributed fault detection of wireless sensor networks , 2006, DIWANS '06.