I（FIB）F：用于命名数据网中路由的迭代布隆过滤器
I(FIB)F: Iterated Bloom Filters for Routing in Named Data Networks
摘要：
命名数据网为高效的内容分发提供了未来互联网的全新设计。由于物联网预计将构成未来互联网的重要组成部分，因此大多数内容将由受限设备管理。这样的设备通常配备有有限的CPU、存储器、带宽和能量供应。然而，目前的命名数据网设计忽略了物联网场景的具体要求，许多数据结构需要进一步优化。本研究的目的是提供一个有效的策略，在命名数据网的路由，通过构建一个转发信息库使用迭代布隆过滤器定义为I（FIB）F。我们建议使用基于迭代哈希的内容名称。该策略减少了数据包的开销。此外，转发策略中所需的存储器和复杂度低于当前解决方案。我们比较我们的建议与解决方案的基础上，分层名称和标准布隆过滤器。我们展示了如何进一步优化I（FIB）F通过利用层次内容名称中包含的结构信息。最后，可以遵循两种策略来减少：（i）用于路由的总存储器或（ii）误报的概率。
英文摘要：
Named Data Networks provide a clean-slate redesign of the Future Internet for efficient content distribution. Because Internet of Things are expected to compose a significant part of Future Internet, most content will be managed by constrained devices. Such devices are often equipped with limited CPU, memory, bandwidth, and energy supply. However, the current Named Data Networks design neglects the specific requirements of Internet of Things scenarios and many data structures need to be further optimised. The purpose of this research is to provide an efficient strategy to route in Named Data Networks by constructing a Forwarding Information Base using Iterated Bloom Filters defined as I(FIB)F. We propose the use of content names based on iterative hashes. This strategy leads to reduce the overhead of packets. Moreover, the memory and the complexity required in the forwarding strategy are lower than in current solutions. We compare our proposal with solutions based on hierarchical names and Standard Bloom Filters. We show how to further optimise I(FIB)F by exploiting the structure information contained in hierarchical content names. Finally, two strategies may be followed to reduce: (i) the overall memory for routing or (ii) the probability of false positives.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
