On mobile sensor data collection using data mules

Arun Das, Anisha Mazumder, Arunabha Sen, N. Mitton
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引用次数: 6

Abstract

The sensor data collection problem using data mules has been studied fairly extensively in the literature. However, in most of these studies, while the mule is mobile, all sensors are stationary. The objective of most of these studies is to minimize the time needed by the mule to collect data from all the sensors and return to the data collection point from where it embarked on its data collection journey. The problem studied in this paper has two major differences with these earlier studies. First, in this study we assume that both the mule as well as the sensors are mobile. Second, we do not attempt to minimize the data collection time. Instead, we minimize the number of mules that will be needed to collect data from all the sensors, subject to the constraint that the data collection process has to be completed within some pre-specified time. We show that the mule minimization problem is NP-Complete and analyze the problem in two settings. We provide solutions to the problem in both settings by first transforming the problem to a generalized version of the minimum flow problem in a network, and then solving it optimally using Integer Linear Programming. Finally, we evaluate our algorithms through experiments and present our results.
利用数据骡子对移动传感器进行数据采集
使用数据骡子的传感器数据收集问题已经在文献中得到了相当广泛的研究。然而,在大多数这些研究中,当骡子移动时,所有传感器都是静止的。大多数这些研究的目标是最大限度地减少骡子从所有传感器收集数据并从开始收集数据的地方返回数据采集点所需的时间。本文研究的问题与早期的研究有两个主要的不同之处。首先,在本研究中,我们假设骡子和传感器都是可移动的。其次,我们不试图最小化数据收集时间。相反,我们最大限度地减少了从所有传感器收集数据所需的骡子数量,并遵守数据收集过程必须在某些预先指定的时间内完成的约束。证明了骡子最小化问题是np完全的,并在两种情况下对问题进行了分析。我们首先将问题转化为网络中最小流量问题的广义版本,然后使用整数线性规划对其进行最优求解,从而为这两种情况下的问题提供了解决方案。最后,我们通过实验来评估我们的算法并给出我们的结果。
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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