Advanced Principal Component-Based Compression Schemes for Wireless Sensor Networks

C. Anagnostopoulos, S. Hadjiefthymiades
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引用次数: 26

Abstract

This article proposes two models that improve the Principal Component-based Context Compression (PC3) model for contextual information forwarding among sensor nodes in a Wireless Sensor Network (WSN). The proposed models (referred to as iPC3 and oPC3) address issues associated with the control of multivariate contextual information transmission in a stationary WSN. Because WSN nodes are typically battery equipped, the primary design goal of the models is to optimize the amount of energy used for data transmission while retaining data accuracy at high levels. The proposed energy conservation techniques and algorithms are based on incremental principal component analysis and optimal stopping theory. iPC3 and oPC3 models are presented and compared with PC3 and other models found in the literature through simulations. The proposed models manage to extend the lifetime of a WSN application by improving energy efficiency within WSN.
无线传感器网络中基于主成分的高级压缩方案
本文提出了两个改进基于主成分的上下文压缩(PC3)模型的模型,用于无线传感器网络(WSN)中传感器节点之间的上下文信息转发。所提出的模型(称为iPC3和oPC3)解决了与固定WSN中多变量上下文信息传输控制相关的问题。由于WSN节点通常配备电池,因此模型的主要设计目标是优化用于数据传输的能量,同时保持高水平的数据准确性。提出了基于增量主成分分析和最优停车理论的节能技术和算法。提出了iPC3和oPC3模型,并通过仿真与PC3和文献中发现的其他模型进行了比较。所提出的模型通过提高WSN内的能量效率来延长WSN应用的生命周期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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