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论文作者:www.51lunwen.org论文属性:本科毕业论文 Thesis登出时间:2014-12-24编辑:Cinderella点击率:11566
论文字数:5763论文编号:org201412192102465262语种:英语 English地区:澳大利亚价格:免费论文
关键词:human migrationmobility concept人类迁移流动性
摘要:本文介绍了人类流动性,尤其突出了人类流动数据对互联网络研究工作的重要意义。
BACKGROUND
Statistical studies on human mobility reveal that the tendencies of human movement are likely to result from deliberate intentions by humans when deciding their destinations. They are not mainly caused by geographical limitations such as boundaries, physical roads and other physical features like buildings. On the contrary, these constraints only limit flight lengths hence causing discontinuities in the statistical trends of human mobility (Rhee, n.d). These findings form a basis of different mobility models that follow human movement patterns that may be expected in outdoor human mobile networks and outdoor environments. For instance, the Levy walk mobility pattern is a model that can be used to demonstrate various statistical patterns.
The widespread adoption of mobile phones has happened in an age where migration is characterized by rapid increase in urbanization in many developing countries. International migrants are also on the rise with people from the developing states accounting for a greater part of the population. This migration may be voluntary or otherwise. Through this mobility, people are able to maintain communication with others, thanks to mobile phones, besides creating new networks. Human mobility is therefore defined as the physical movement of individuals from one place to another. It can be over short or long distances and people can move as individuals or in groups, happening either voluntarily or involuntarily within own country or across borders (International Organization for Migration, 2008).
MOBILITY MODELS
Human mobility models attempt to describe human movements in different scenarios. Categorically, the models are based on the nature of the entity that invokes the movement, particularly the behavior of that entity. An entity mobility model considers the movement of an individual which means that multiple entities are predicted independently. Examples of entity mobility models discussed in this study are the Random Walk, Random Waypoint, Random Direction, Manhattan and the Gauss-Markov models. In contrast, group mobility models predict a number of individual entities as a group which is taken to be moving as a whole. The entities are related to each other in movement. In fact, group mobility models are arguably more realistic that entity mobility models. This is because human beings move in a way that they are not independent from one another. For example, people usually walk around collectively or towards the same direction. Several illustrations of group mobility models are discussed under this s本论文由英语论文网提供整理,提供论文代写,英语论文代写,代写论文,代写英语论文,代写留学生论文,代写英文论文,留学生论文代写相关核心关键词搜索。