MobCCN:一种符合ccn的协议,用于物联网环境中具有机会接触的数据收集

E. Borgia, R. Bruno, A. Passarella
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引用次数: 8

摘要

在物联网环境中,可以预期很大一部分服务与生成数据的物理区域相关并与之相关联。这是由于物联网设备与其所在的物理环境之间的典型紧密联系。此外,通信模式可能在很大程度上以内容为中心,而不是以设备为中心,因为人们关心的是获取数据,而不管数据在哪里生成或存储。在本文中,我们提出了MobCCN,这是一种以内容为中心的网络协议,用于支持微型物联网设备(如传感器)和用户个人移动设备(如智能手机)存在的数据传输。MobCCN将机会网络技术(支持情境化、基于接近的通信)和信息中心网络(ICN)结合在一起,以支持以内容为中心的通信模式。MobCCN定义了一种新的类似ccn的路由和转发算法,该算法通过估计节点之间、节点之间以及网络中产生和存储的数据之间的接触率,动态构建基于梯度的内容传播图。在保持与标准CCN机制的兼容性的同时,MobCCN算法使CCN路由和转发适合机会网络环境。我们已经在CCN-lite中实现了MobCCN,这是CCN事实上的标准轻量级实现,适用于资源受限的设备。仿真结果验证了该方法在可扩展性和效率方面的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MobCCN: a CCN-compliant protocol for data collection with opportunistic contacts in IoT environments
In IoT environments, a significant fraction of services can be expected to be relevant and contextualised to the physical area where data is generated. This is due to the typical strong bond between IoT devices and the physical environment where they are located. Moreover, communication patterns may be largely content-centric rather than device-centric, as interest would be in getting the data, irrespective of where they are generated or stored. In this paper we propose MobCCN, a content-centric network protocol to support data delivery in presence of tiny IoT devices (such as sensors) and users' personal mobile devices (such as smartphones). MobCCN joins together opportunistic networking techniques (to support contextualised, proximity-based communications) and Information Centric Networking (ICN) to support content-centric communication patterns. MobCCN defines a new CCN-like routing and forwarding algorithm, which dynamically builds a gradient-based content-dissemination graph using estimates of the contact rates between nodes, and between nodes and the data that is produced and stored in the network. While preserving compatibility with the standard CCN mechanisms, the MobCCN algorithm makes CCN routing and forwarding suitable for opportunistic networking environments. We have implemented MobCCN in CCN-lite, a de-facto standard lightweight implementation of CCN, which is suitable for resource-constrained devices. Simulation results confirm the feasibility of the proposed approach both in terms of scalability and efficiency.
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