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TPS_DR: A Universal Dimension Reducing Algorithm for Optimal Trust Path Selection in Complex Sensor Network |
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PP: 161-167 |
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Author(s) |
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Guangquan Xu,
Xiuming Tian,
Xiaochun Cao,
Xiaohong Li,
Zhiyong Feng,
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Abstract |
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| Energy efficiency, one of the key factors for sensor network, is a challenging work. It is agreed that sink routing is the main
influencing factor for energy efficiency and selecting an optimal routing path becomes critical. It is hard for source participant (sink
nodes, namely trustor) to select a trustworthy target participant (data collecting sensor nodes, namely trustee), especially when the scale
of sensor network becomes increasingly larger. An optimal trust path selection problem (TPS problem) is a Multi-Constrained Optimal
Path (MCOP) problem, which is proved to be a NP-Complete problem. In this paper, we first introduce a concept of complex trust
network to model the relationships among network nodes in a complex sensor network. In this model, we represent the trust network
based on high dimensional vector and matrix. Then, we propose an algorithm TPS DR (Trust Path Selection based on Dimensionality
Reduction) to simplify the trust network through reducing the dimensionality, i.e. cluster some similar nodes into a supernode. Our
example demonstrates the usage and advantage of our model and algorithm. |
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