Planning and Scaling a Named Data Network with Persistent Identifier Interoperability

Research clouds contain diverse and large datasets, this data is published by the use of

Persistent Identiers (PIDs). The current paradigm utilizes data transmissions by the means

of host-to-host connections (IP), where every data request from the consumer is answered

with a data transfer from the source (the producer). This approach can potentially cause

congestion and delays with many data consumers. Named Data Networking (NDN) is a

data centric approach where unique data, once requested, is stored on intermediate hops

in the network. Consecutive requests for that unique data object are then made available

by these intermediate hops (caching). This approach distributes trac load more ecient

and reliable compared to host-to-host connection oriented techniques [69]. Furthermore, one

of the most important technical challenges is to incorporate interoperability between NDN

and the dierent PID naming schemas. These naming schemas are used by data providers

within these data infrastructures for sharing and identifying digital objects. This research

investigated how identication services and transmission services can be better integrated

by the use of NDN. In order to create this integration, a translation between the dierent

naming schemas was developed and made extendable for future PID types. Furthermore,

a method was researched and applied for planning and scaling an NDN with scalability in

mind.