54 research outputs found
Stationary Distribution of a Generalized LRU-MRU Content Cache
Many different caching mechanisms have been previously proposed, exploring
different insertion and eviction policies and their performance individually
and as part of caching networks. We obtain a novel closed-form stationary
invariant distribution for a generalization of LRU and MRU caching nodes under
a reference Markov model. Numerical comparisons are made with an "Incremental
Rank Progress" (IRP a.k.a. CLIMB) and random eviction (a.k.a. random
replacement) methods under a steady-state Zipf popularity distribution. The
range of cache hit probabilities is smaller under MRU and larger under IRP
compared to LRU. We conclude with the invariant distribution for a special case
of a random-eviction caching tree-network and associated discussion
A versatile and accurate approximation for LRU cache performance
In a 2002 paper, Che and co-authors proposed a simple approach for estimating
the hit rates of a cache operating the least recently used (LRU) replacement
policy. The approximation proves remarkably accurate and is applicable to quite
general distributions of object popularity. This paper provides a mathematical
explanation for the success of the approximation, notably in configurations
where the intuitive arguments of Che, et al clearly do not apply. The
approximation is particularly useful in evaluating the performance of current
proposals for an information centric network where other approaches fail due to
the very large populations of cacheable objects to be taken into account and to
their complex popularity law, resulting from the mix of different content types
and the filtering effect induced by the lower layers in a cache hierarchy
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
The Price of Updating the Control Plane in Information-Centric Networks
We are studying some fundamental properties of the interface between control
and data planes in Information-Centric Networks. We try to evaluate the traffic
between these two planes based on allowing a minimum level of acceptable
distortion in the network state representation in the control plane. We apply
our framework to content distribution, and see how we can compute the overhead
of maintaining the location of content in the control plane. This is of
importance to evaluate content-oriented network architectures: we identify
scenarios where the cost of updating the control plane for content routing
overwhelms the benefit of fetching a nearby copy. We also show how to minimize
the cost of this overhead when associating costs to peering traffic and to
internal traffic for operator-driven CDNs.Comment: 10 pages, 12 figure
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