1,589 research outputs found
A unified approach to the performance analysis of caching systems
We propose a unified methodology to analyse the performance of caches (both
isolated and interconnected), by extending and generalizing a decoupling
technique originally known as Che's approximation, which provides very accurate
results at low computational cost. We consider several caching policies, taking
into account the effects of temporal locality. In the case of interconnected
caches, our approach allows us to do better than the Poisson approximation
commonly adopted in prior work. Our results, validated against simulations and
trace-driven experiments, provide interesting insights into the performance of
caching systems.Comment: in ACM TOMPECS 20016. Preliminary version published at IEEE Infocom
201
On Resource Pooling and Separation for LRU Caching
Caching systems using the Least Recently Used (LRU) principle have now become
ubiquitous. A fundamental question for these systems is whether the cache space
should be pooled together or divided to serve multiple flows of data item
requests in order to minimize the miss probabilities. In this paper, we show
that there is no straight yes or no answer to this question, depending on
complex combinations of critical factors, including, e.g., request rates,
overlapped data items across different request flows, data item popularities
and their sizes. Specifically, we characterize the asymptotic miss
probabilities for multiple competing request flows under resource pooling and
separation for LRU caching when the cache size is large.
Analytically, we show that it is asymptotically optimal to jointly serve
multiple flows if their data item sizes and popularity distributions are
similar and their arrival rates do not differ significantly; the
self-organizing property of LRU caching automatically optimizes the resource
allocation among them asymptotically. Otherwise, separating these flows could
be better, e.g., when data sizes vary significantly. We also quantify critical
points beyond which resource pooling is better than separation for each of the
flows when the overlapped data items exceed certain levels. Technically, we
generalize existing results on the asymptotic miss probability of LRU caching
for a broad class of heavy-tailed distributions and extend them to multiple
competing flows with varying data item sizes, which also validates the Che
approximation under certain conditions. These results provide new insights on
improving the performance of caching systems
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
Performance Evaluation of Caching Policies in NDN - an ICN Architecture
Information Centric Networking (ICN) advocates the philosophy of accessing
the content independent of its location. Owing to this location independence in
ICN, the routers en-route can be enabled to cache the content to serve the
future requests for the same content locally. Several ICN architectures have
been proposed in the literature along with various caching algorithms for
caching and cache replacement at the routers en-route. The aim of this paper is
to critically evaluate various caching policies using Named Data Networking
(NDN), an ICN architecture proposed in literature. We have presented the
performance comparison of different caching policies naming First In First Out
(FIFO), Least Recently Used (LRU), and Universal Caching (UC) in two network
models; Watts-Strogatz (WS) model (suitable for dense short link networks such
as sensor networks) and Sprint topology (better suited for large Internet
Service Provider (ISP) networks) using ndnSIM, an ns3 based discrete event
simulator for NDN architecture. Our results indicate that UC outperforms other
caching policies such as LRU and FIFO and makes UC a better alternative for
both sensor networks and ISP networks
A Study on the Influence of Caching: Sequences of Dense Linear Algebra Kernels
It is universally known that caching is critical to attain high- performance
implementations: In many situations, data locality (in space and time) plays a
bigger role than optimizing the (number of) arithmetic floating point
operations. In this paper, we show evidence that at least for linear algebra
algorithms, caching is also a crucial factor for accurate performance modeling
and performance prediction.Comment: Submitted to the Ninth International Workshop on Automatic
Performance Tuning (iWAPT2014
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
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