The growth in interest and technologies surrounding data availability, portability, and aggregation has ramifications on design and development of applications outside the social network space.
随着人们对数据有效性、可移植性与聚合等话题的兴致和技术的增长，这一趋势也波及到社会网络领域以外的应用程序设计和开发。
To solve the contradiction problem, a lightweight, energy efficient, in-network lossless aggregation and hierarchical cluster was proposed based on data collecting mechanism (QTBDC).
为解决上述矛盾问题，提出了一种轻量级的、能量有效的、基于无损聚合的层次分簇数据收集机制(QTBDC)。
In order to reduce the energy consumption and ensure the security in wireless sensor network, the secure data aggregation algorithm based on pattern codes was designed.
为了降低无线传感器网络能耗，保障网络安全，设计了一种基于模式码的安全数据融合算法。
According to the research of theory and experiment, the data aggregation technology based on neural network in WSN proposed in this thesis is applied to machinery fault diagnosis.
在理论和实验研究的基础上，将所提出的基于神经网络的WSN数据融合的方法进行机械故障诊断。
Nowadays, data aggregation is hotspot of research in wireless sensor network, and is one of important technology about saving energy.
数据聚合技术是目前无线传感器网络中的研究热点，同时也是一种重要的节能技术之一。
Nowadays, data aggregation is hotspot of research in wireless sensor network, and is one of important technology about saving energy.
数据聚合技术是目前无线传感器网络中的研究热点，同时也是一种重要的节能技术之一。
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