假期无线传感器网络寿命节能问题的正态分布

Shkelqim Hajrulla, Taylan Demi̇r, Loubna Ali, Nour Souli̇man
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引用次数: 0

摘要

基于数学运算,我们可以对无线传感器网络的寿命节能做一些分析。我们将用数值方法研究假期时间,以研究解析模型中的节能机理。几篇研究论文报道,随机变量的正态分布在分析和比较数据方面有巨大的贡献,根据所使用的方法或观察生活应用中许多事件的趋势,使过程更容易。本文通过解决WSN节点运行的实际问题,重点分析了两个问题:一是正态分布及其特例;二是标准正态分布的应用,涉及一定时间间隔内休假时间的节能问题。我们的工作目标是获得合适的算法,使网络休假期间的数据丢失风险最小化,这与这段时间后网络节点结构的组织有关,并使单个传感器的电池寿命最大化。为此,我们将使用数学方法,并基于概率分布理论,我们推导出从任意固定时间到可变时间t的处理周期持续时间的一些分布。基于拉普拉斯变换和拉格朗日方法概念的解析方法比以前的结果表现得更好。我们继续通过详细的计算和图表来检验它们。我们将预测的节能与平均实际能耗进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Normal Distribution on Energy Saving Problem for the Wireless Sensor Network Life on the Vacation Period
Based on math operations, we can do some analytic approaches for the energy saving for the WSN life. We will study the vacation period time using numerical methods for studding the energy saving mechanism in analytic models. Several research papers have reported that the normal distribution of a random variable has an enormous contribution in analyzing and comparing the data with each other, making the process easier according to methods used or observing the tendencies of numerous occurrences in life applications. This paper focuses on analyzing two problems: the first one is the normal distribution and its special cases by solving real problems of WSN node operations and the second one is the application of standard normal distribution relate to saving energy during vacation time in a certain time interval. The goal of our work is to obtain the appropriate algorithm to minimize the risk of data loss during the network vacation period, which is associated with the organization of network node structures after this period time, and to maximize the battery life of individual sensors. For that, we will use math methods and based on probability distribution theory, we derive some distributions of the processing period duration from an arbitrary fixed time up to a variable time t. The analytic approach based on the conception of Laplace transform and the Lagrange method performs better than the previous results. We continue by examining them through detailed calculations and graphs. We compare the predicted energy saving and the average real energy.
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