TPS_DR: A Universal Dimension Reducing Algorithm for Optimal Trust Path Selection in Complex Sensor Network

Abstract

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.