THESIS
2021
1 online resource (xiv, 111 pages) : illustrations (some color)
Abstract
Caching has become an integral part of the Internet to improve the performance of
services and applications that rely on the Internet as a medium to disseminate information
and content. Information-centric networks (ICN) is an alternative paradigm to reconstruct
the Internet that puts information and content as the first class citizens. Under such
paradigm, caching is natively supported in the network layer. In this thesis, we address
the inefficiencies resulting from the default caching strategy employed by ICN forwarders,
and discuss the design and implementation of two caching schemes that improve caching
in the spatial and temporal dimensions.
In the spatial dimension, we introduce cooperative caching. Forwarders share their
caches with one-hop neighbors while evicting redundant cac...[
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Caching has become an integral part of the Internet to improve the performance of
services and applications that rely on the Internet as a medium to disseminate information
and content. Information-centric networks (ICN) is an alternative paradigm to reconstruct
the Internet that puts information and content as the first class citizens. Under such
paradigm, caching is natively supported in the network layer. In this thesis, we address
the inefficiencies resulting from the default caching strategy employed by ICN forwarders,
and discuss the design and implementation of two caching schemes that improve caching
in the spatial and temporal dimensions.
In the spatial dimension, we introduce cooperative caching. Forwarders share their
caches with one-hop neighbors while evicting redundant cache entries. We make several
design decisions to make this scheme practical to implement. In the temporal dimension,
we explore the use of machine learning methods to construct a model that is used to
predict future content popularity based on past history, and design a cache algorithm
that uses predicted popularity to make cache decisions. We evaluate the caching schemes
by extensive emulations of network traffic on emulated network topologies.
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