3,337 research outputs found
Temporal Locality in Today's Content Caching: Why it Matters and How to Model it
The dimensioning of caching systems represents a difficult task in the design
of infrastructures for content distribution in the current Internet. This paper
addresses the problem of defining a realistic arrival process for the content
requests generated by users, due its critical importance for both analytical
and simulative evaluations of the performance of caching systems. First, with
the aid of YouTube traces collected inside operational residential networks, we
identify the characteristics of real traffic that need to be considered or can
be safely neglected in order to accurately predict the performance of a cache.
Second, we propose a new parsimonious traffic model, named the Shot Noise Model
(SNM), that enables users to natively capture the dynamics of content
popularity, whilst still being sufficiently simple to be employed effectively
for both analytical and scalable simulative studies of caching systems.
Finally, our results show that the SNM presents a much better solution to
account for the temporal locality observed in real traffic compared to existing
approaches.Comment: 7 pages, 7 figures, Accepted for publication in ACM Computer
Communication Revie
Catalog Dynamics: Impact of Content Publishing and Perishing on the Performance of a LRU Cache
The Internet heavily relies on Content Distribution Networks and transparent
caches to cope with the ever-increasing traffic demand of users. Content,
however, is essentially versatile: once published at a given time, its
popularity vanishes over time. All requests for a given document are then
concentrated between the publishing time and an effective perishing time.
In this paper, we propose a new model for the arrival of content requests,
which takes into account the dynamical nature of the content catalog. Based on
two large traffic traces collected on the Orange network, we use the
semi-experimental method and determine invariants of the content request
process. This allows us to define a simple mathematical model for content
requests; by extending the so-called "Che approximation", we then compute the
performance of a LRU cache fed with such a request process, expressed by its
hit ratio. We numerically validate the good accuracy of our model by comparison
to trace-based simulation.Comment: 13 Pages, 9 figures. Full version of the article submitted to the ITC
2014 conference. Small corrections in the appendix from the previous versio
Unravelling the Impact of Temporal and Geographical Locality in Content Caching Systems
To assess the performance of caching systems, the definition of a proper
process describing the content requests generated by users is required.
Starting from the analysis of traces of YouTube video requests collected inside
operational networks, we identify the characteristics of real traffic that need
to be represented and those that instead can be safely neglected. Based on our
observations, we introduce a simple, parsimonious traffic model, named Shot
Noise Model (SNM), that allows us to capture temporal and geographical locality
of content popularity. The SNM is sufficiently simple to be effectively
employed in both analytical and scalable simulative studies of caching systems.
We demonstrate this by analytically characterizing the performance of the LRU
caching policy under the SNM, for both a single cache and a network of caches.
With respect to the standard Independent Reference Model (IRM), some
paradigmatic shifts, concerning the impact of various traffic characteristics
on cache performance, clearly emerge from our results.Comment: 14 pages, 11 Figures, 2 Appendice
ISP-friendly Peer-assisted On-demand Streaming of Long Duration Content in BBC iPlayer
In search of scalable solutions, CDNs are exploring P2P support. However, the
benefits of peer assistance can be limited by various obstacle factors such as
ISP friendliness - requiring peers to be within the same ISP, bitrate
stratification - the need to match peers with others needing similar bitrate,
and partial participation - some peers choosing not to redistribute content.
This work relates potential gains from peer assistance to the average number
of users in a swarm, its capacity, and empirically studies the effects of these
obstacle factors at scale, using a month-long trace of over 2 million users in
London accessing BBC shows online. Results indicate that even when P2P swarms
are localised within ISPs, up to 88% of traffic can be saved. Surprisingly,
bitrate stratification results in 2 large sub-swarms and does not significantly
affect savings. However, partial participation, and the need for a minimum
swarm size do affect gains. We investigate improvements to gain from increasing
content availability through two well-studied techniques: content bundling -
combining multiple items to increase availability, and historical caching of
previously watched items. Bundling proves ineffective as increased server
traffic from larger bundles outweighs benefits of availability, but simple
caching can considerably boost traffic gains from peer assistance.Comment: In Proceedings of IEEE INFOCOM 201
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