Data reduction in MANETs using forward feature construction technique

B. Mahapatra, S. Patnaik
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引用次数: 3

Abstract

With limited resource of nodes in Manets, achieving efficiency of a resilient and a secured network is always a challenge. Implementing any algorithm to enhance performance in such a node may result in lowering the lifetime of the network and affects the efficiency of the nodes adversely. Data regression on an incoming data in a node makes the Algorithm more efficient with respect to time and space thereby improving the performance. Apart from that the Algorithm also removes the noise factor from the data before it undergoes any process. The paper proposes the idea of preprocessing the incoming data into a node in a Manet using Sequential Feature Analysis as a Data regression Technique.
基于前向特征构建技术的manet数据约简
由于Manets节点资源有限,实现弹性和安全网络的效率一直是一个挑战。在这样的节点上实现任何提高性能的算法都可能导致降低网络的生命周期,并对节点的效率产生不利影响。对一个节点的传入数据进行数据回归,使算法在时间和空间上更有效率,从而提高性能。除此之外,该算法还在数据经过任何处理之前从数据中去除噪声因素。本文提出了使用序列特征分析作为数据回归技术对输入数据进行预处理的思想。
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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