Data gathering with multi-attribute fusion in wireless sensor networks
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 mi...
| Main Authors: | , , , |
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| Format: | Book Chapter |
| Language: | English English |
| Published: |
IGI Global Publishers
2011
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/578/ http://irep.iium.edu.my/578/ http://irep.iium.edu.my/578/ http://irep.iium.edu.my/578/1/Sakib-KaiLin-chapter.pdf http://irep.iium.edu.my/578/4/Chp_8.pdf |
| Summary: | 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 is concluded by identifying some open research issues on this topic. |
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