Study on Data Fusion Techniques in Wireless Sensor Networks

In wireless sensor networks or WSNs, to improve the accuracy and correctness of the target sensing and monitoring, individual nodes often have overlapping sensing ranges. This usually generates data redundancy and results in both time and power consumption especially when large amount of similar data are to be transmitted. Data fusion scheme takes the advantage of this overlapping feature and can reduce, delete and refine the redundant data in the process of data transmission. A survey is presented in this article studying on the data fusion techniques in WSNs from the aspects of cluster based schemes, chain based schemes to statistics based schemes. Their advantages and disadvantages are also discussed in this research.

[1]  Félix Gómez Mármol,et al.  Towards pre-standardization of trust and reputation models for distributed and heterogeneous systems , 2010, Comput. Stand. Interfaces.

[2]  Yong Zhang,et al.  A novel reputation computation model based on subjective logic for mobile ad hoc networks , 2011, Future Gener. Comput. Syst..

[3]  K. Komathy,et al.  Trust-based evolutionary game model assisting AODV routing against selfishness , 2008, J. Netw. Comput. Appl..

[4]  Brian L. Mark,et al.  E-Hermes: A robust cooperative trust establishment scheme for mobile ad hoc networks , 2009, Ad Hoc Networks.

[5]  Cyrus Shahabi,et al.  The Clustered AGgregation (CAG) technique leveraging spatial and temporal correlations in wireless sensor networks , 2007, TOSN.

[6]  Azzedine Boukerche,et al.  A trust-based security system for ubiquitous and pervasive computing environments , 2008, Comput. Commun..

[7]  Weiming Zhang,et al.  A Novel Cluster-Based Data Fusion Algorithm for Wireless Sensor Networks , 2011, 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing.

[8]  Frank L. Lewis,et al.  Energy-efficient wireless sensor network design and implementation for condition-based maintenance , 2007, TOSN.

[9]  Sandip Sen,et al.  Comparing Reputation Schemes for Detecting Malicious Nodes in Sensor Networks , 2011, Comput. J..

[10]  Zhe Wei,et al.  Energy-saving reputation method for wireless sensor networks , 2012 .

[11]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[12]  S. Challa,et al.  RBATMWSN: Recursive Bayesian Approach to Trust Management in Wireless Sensor Networks , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[13]  R. Sangeetha,et al.  A Novel Framework for Target Tracking and Data Fusion in Wireless Sensor Networks Using Kernel Based Learning Algorithm , 2011 .

[14]  Adwitiya Sinha,et al.  An integrated fusion protocol for congregating sensor data in wireless sensor network , 2011, 2011 IEEE Symposium on Computers & Informatics.

[15]  N. Sarma,et al.  TREEPSI: tree based energy efficient protocol for sensor information , 2006, 2006 IFIP International Conference on Wireless and Optical Communications Networks.

[16]  Young-Ju Han,et al.  The Concentric Clustering Scheme for Efficient Energy Consumption in the PEGASIS , 2007, The 9th International Conference on Advanced Communication Technology.

[17]  Zhu Han,et al.  A trust evaluation framework in distributed networks: Vulnerability analysis and defense against attacks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[18]  Mani B. Srivastava,et al.  Reputation-based framework for high integrity sensor networks , 2008, TOSN.

[19]  George D. Stamoulis,et al.  Achieving Honest Ratings with Reputation-Based Fines in Electronic Markets , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[20]  Xiang Zhou,et al.  A Trust Evaluation Algorithm for Wireless Sensor Networks Based on Node Behaviors and D-S Evidence Theory , 2011, Sensors.

[21]  Chao Li,et al.  Trust model based on the multinomial subjective logic and risk mechanism for P2P network of file sharing , 2011 .

[22]  Charalampos Konstantopoulos,et al.  An approach for near-optimal distributed data fusion in wireless sensor networks , 2010, Wirel. Networks.

[23]  Shahzad Ali,et al.  Distributed grid based robust clustering protocol for mobile sensor networks , 2011, Int. Arab J. Inf. Technol..

[24]  Violet R. Syrotiuk,et al.  The performance of a watchdog protocol for wireless network security , 2007, Int. J. Wirel. Mob. Comput..

[25]  Krishna M. Sivalingam,et al.  Data Gathering Algorithms in Sensor Networks Using Energy Metrics , 2002, IEEE Trans. Parallel Distributed Syst..

[26]  R. B. Patel,et al.  EECDA: Energy Efficient Clustering and Data Aggregation Protocol for Heterogeneous Wireless Sensor Networks , 2011, Int. J. Comput. Commun. Control.

[27]  Giuseppe Lo Re,et al.  A Network Protocol to Enhance Robustness in Tree-Based WSNs Using Data Aggregation , 2007, 2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems.

[28]  Juan Manuel González Nieto,et al.  RSDA: Reputation-Based Secure Data Aggregation in Wireless Sensor Networks , 2008, 2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies.

[29]  Niki Pissinou,et al.  Cluster-Based Reputation and Trust for Wireless Sensor Networks , 2007, 2007 4th IEEE Consumer Communications and Networking Conference.

[30]  Yacine Challal,et al.  Reliable and fully distributed trust model for mobile ad hoc networks , 2009, Comput. Secur..

[31]  Guanhua Yan,et al.  Mobi-watchdog: you can steal, but you can't run! , 2009, WiSec '09.

[32]  Yajie Fei.  A Data Fusion Strategy of Wireless Sensor Network Based on Specific Application , 2011 .

[33]  Benxiong Huang,et al.  SONR: A reliable reputation system of self-organized network , 2012, J. Netw. Comput. Appl..

[34]  Ruchuan Wang,et al.  Novel Node Localization Algorithm Based on Nonlinear Weighting Least Square for Wireless Sensor Networks , 2012, Int. J. Distributed Sens. Networks.