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A Statistical Mechanics-Based Framework to Analyze Ad Hoc Networks with Random Access

机译:基于统计力学的框架,用于分析随机访问的Ad Hoc网络

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Characterizing the performance of ad hoc networks is one of the most intricate open challenges; conventional ideas based on information-theoretic techniques and inequalities have not yet been able to successfully tackle this problem in its generality. Motivated thus, we promote the totally asymmetric simple exclusion process (TASEP), a particle flow model in statistical mechanics, as a useful analytical tool to study ad hoc networks with random access. Employing the TASEP framework, we first investigate the average end-to-end delay and throughput performance of a linear multihop flow of packets. Additionally, we analytically derive the distribution of delays incurred by packets at each node, as well as the joint distributions of the delays across adjacent hops along the flow. We then consider more complex wireless network models comprising intersecting flows, and propose the partial mean-field approximation (PMFA), a method that helps tightly approximate the throughput performance of the system. We finally demonstrate via a simple example that the PMFA procedure is quite general in that it may be used to accurately evaluate the performance of ad hoc networks with arbitrary topologies.
机译:表征ad hoc网络的性能是最复杂的开放挑战之一。基于信息理论技术和不平等的传统思想尚未能够成功地普遍解决这个问题。因此,我们推动了完全不对称的简单排除过程(TASEP),一种统计力学中的粒子流模型,作为研究随机访问的ad hoc网络的有用分析工具。使用TASEP框架,我们首先研究线性多跳数据包流的平均端到端延迟和吞吐量性能。此外,我们通过分析得出每个节点上数据包引起的延迟分布,以及沿流沿相邻跃点的延迟联合分布。然后,我们考虑包括相交流的更复杂的无线网络模型,并提出部分均值场近似(PMFA),这是一种有助于紧密估计系统吞吐量性能的方法。最后,我们通过一个简单的示例演示了PMFA过程非常普遍,因为它可用于准确评估具有任意拓扑的自组织网络的性能。

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