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Data Gathering with Multi-Attribute Fusion in Wireless Sensor Networks
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Author(s): Kai Lin (Dalian University of Technology, China), Lei Wang (Dalian University of Technology, China), Lei Shu (Osaka University, Japan)and Al-Sakib Khan Pathan (International Islamic University, Malaysia)
Copyright: 2012
Pages: 23
Source title:
Advancements in Distributed Computing and Internet Technologies: Trends and Issues
Source Author(s)/Editor(s): Al-Sakib Khan Pathan (International Islamic University Malaysia (IIUM), Malaysia), Mukaddim Pathan (Commonwealth Scientific and Industrial Research Organization (CSIRO), Australia)and Hae Young Lee (Electronics and Telecommunications Research Institut (ETRI), South Korea)
DOI: 10.4018/978-1-61350-110-8.ch008
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Abstract
This chapter addresses the problem of data gathering with multi-attribute fusion over a bandwidth and energy constrained wireless sensor network (WSN). As there are strong correlations between data gathered from sensor nodes in close physical proximity, effective in-network fusion schemes involve minimizing such redundancy and hence reducing the load in wireless sensor networks. Considering a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets; hence, the complexity for the fusion process is increased due to the existence of various physical attributes. In this chapter, by investigating the process and performance of multi-attribute fusion in data gathering of WSNs, we design a self-adaptive threshold to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Then, a novel energy equilibrium routing method is proposed to balance and save energy in WSNs, which is named multi-attribute fusion tree (MAFT). The establishment of MAFT is determined by the remaining energy of sensor nodes and the energy-conservation efficiency of data fusion. Finally, the energy saving performance of the scheme is demonstrated through comprehensive simulations. The chapter concludes by identifying some open research issues on this topic.
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