Stochastic Properties of Mobility Models in Mobile Ad Hoc Networks
Stochastic Properties of Mobility Models in Mobile Ad Hoc Networks
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DOI：
10.1109/ciss.2006.286649
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发表时间：
2006-03
期刊：
影响因子：
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通讯作者：
S. Bandyopadhyay;E. Coyle;Tillmann Falck
中科院分区：
文献类型：
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作者：
S. Bandyopadhyay;E. Coyle;Tillmann Falck
用于控制移动自组织网络中节点移动性的随机模型对网络的覆盖范围、最大吞吐量和可实现的吞吐量-延迟权衡具有重要影响。在本文中，我们基于在固定时间内访问状态的数量，访问区域内每个状态的时间，以及漫游节点数量对首次进入一组状态的时间的影响，比较了几种移动性模型，包括随机行走模型，随机路径点模型和曼哈顿模型。我们还考虑了基于相关随机游走的迁移模型，该模型可以解释时间依赖性、地理限制和非零漂移。我们证明了这些模型是解析可处理的，通过使用矩阵分析方法在时间域和变换域为半无限和有限一维晶格的节点在任何时间的任何位置的概率推导出新的封闭形式的结果。我们还推导了这些步行的首次入口时间分布。我们发现，与具有相同平均过渡率的随机漫步相比，相关随机漫步(i)在给定的时间内覆盖更多的地面，并且完全覆盖一个区域所需的时间更短；（ii）与随机路径点和随机行走模型相比，到达小状态集的首次进入时间更短；（iii）在稳态下导致节点均匀分布（边界处除外）。
The stochastic model assumed to govern the mobility of nodes in a mobile ad hoc network has a significant impact on the network's coverage, maximum throughput, and achievable throughput-delay tradeoffs. In this paper, we compare several mobility models, including the random walk, random waypoint and Manhattan models, on the basis of the number of states visited in a fixed time, the time to visit every state in a region, and the effect of the number of wandering nodes on the time to first entrance to a set of states. We also consider mobility models based on correlated random walks, which can account for time dependency, geographical restrictions, and nonzero drift. We demonstrate that these models are analytically tractable by using a matrix analytic approach to derive new, closed-form results in both the time- and transform-domains for the probability that a node is at any location at any time for both semi-infinite and finite one-dimensional lattices. We also derive first entrance time distributions for these walks. We find that a correlated random walk (i) covers more ground in a given amount of time and takes a smaller amount of time to cover an area completely than a random walk with the same average transition rate; (ii) has a smaller first entrance time to small sets of states than the random waypoint and random walk models and (iii) leads to uniform distribution of nodes (except at the boundaries) in steady state.