University of Cambridge > Talks.cam > Computer Laboratory Systems Research Group Seminar > I(FIB)F: Iterated Bloom Filters for Routing in Named Data Networks

I(FIB)F: Iterated Bloom Filters for Routing in Named Data Networks

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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.

Bio: Cristina is a postdoctoral researcher awarded by the Swiss National Science Foundation with an Early Postdoc.Mobility fellowship. She obtained her Ph.D. degree in Computer Science at the University of Geneva in 2016. Her research interests are focused on the development of the future Internet and its security challenges. Of particular interest is the improvement of content distribution networks as Named Data Networks.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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