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首页> 外文期刊>IEEE systems journal >An Analytical Model for Information Centric Internet of Things Networks in Opportunistic Scenarios
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An Analytical Model for Information Centric Internet of Things Networks in Opportunistic Scenarios

机译：机会主义情景中信息网络网络信息互联网的分析模型

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摘要

The availability of environmental monitoring data collected by Internet of Things networks can be essential for many critical processes, such as relief operations in disaster areas. The underlying communications infrastructure can be however severely compromised in these scenarios and therefore opportunistic approaches might be needed. Approaches based on information centric networks (ICN), where moving devices forward collected data, have been proposed for opportunistic scenarios but to date, the dynamics of the delivery process in ICNs remain poorly understood. In this paper, we build a family of Markovian models for the delivery process of ICNs in opportunistic scenarios, that allow us to derive the end-to-end delay distribution and the storage ratio in terms of the encounter rate of the moving devices. Furthermore, we investigate how prefetching mechanisms affect the delivery process compared to conventional ICNs. The proposed models are fully validated in a computer simulation environment and demonstrate that the utility of delivery with prefetching reaches its peak in a short time and then decreases at a high rate. Our Markovian models can provide both the insight and quantitative estimations that are needed to design practical ICNs in opportunistic scenarios.
机译：内贸易赛网收集的环境监测数据的可用性对于许多关键过程至关重要，例如灾区救济操作。然而，在这些情景中，潜在的通信基础设施可以严重损害，因此可能需要机会主义方法。基于信息中心网络（ICN）的方法，其中移动设备前进收集的数据，已经为机会主义的情景提出，但到目前为止，ICN中的交付过程的动态仍然明白很差。在本文中，我们构建了一个Markovian模型的家庭，用于在机会主义方案中为ICN的交付过程，允许我们在移动设备的遇到速率方面导出端到端延迟分布和存储比率。此外，我们研究了与传统ICN相比如何影响递送过程的预取机制。所提出的模型在计算机仿真环境中完全验证，并证明递送预取的效用在短时间内达到其峰值，然后以高速速度降低。我们的Markovian模型可以提供在机会主义情景中设计实用ICN所需的洞察力和定量估计。

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