1,395 research outputs found
Impact of traffic mix on caching performance in a content-centric network
For a realistic traffic mix, we evaluate the hit rates attained in a
two-layer cache hierarchy designed to reduce Internet bandwidth requirements.
The model identifies four main types of content, web, file sharing, user
generated content and video on demand, distinguished in terms of their traffic
shares, their population and object sizes and their popularity distributions.
Results demonstrate that caching VoD in access routers offers a highly
favorable bandwidth memory tradeoff but that the other types of content would
likely be more efficiently handled in very large capacity storage devices in
the core. Evaluations are based on a simple approximation for LRU cache
performance that proves highly accurate in relevant configurations
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
Exploring the Memory-Bandwidth Tradeoff in an Information-Centric Network
An information-centric network should realize significant economies by
exploiting a favourable memory-bandwidth tradeoff: it is cheaper to store
copies of popular content close to users than to fetch them repeatedly over the
Internet. We evaluate this tradeoff for some simple cache network structures
under realistic assumptions concerning the size of the content catalogue and
its popularity distribution. Derived cost formulas reveal the relative impact
of various cost, traffic and capacity parameters, allowing an appraisal of
possible future network architectures. Our results suggest it probably makes
more sense to envisage the future Internet as a loosely interconnected set of
local data centers than a network like today's with routers augmented by
limited capacity content stores.Comment: Proceedings of ITC 25 (International Teletraffic Congress), Shanghai,
September, 201
Poor Man's Content Centric Networking (with TCP)
A number of different architectures have been proposed in support of data-oriented or information-centric networking. Besides a similar visions, they share the need for designing a new networking architecture. We present an incrementally deployable approach to content-centric networking based upon TCP. Content-aware senders cooperate with probabilistically operating routers for scalable content delivery (to unmodified clients), effectively supporting opportunistic caching for time-shifted access as well as de-facto synchronous multicast delivery. Our approach is application protocol-independent and provides support beyond HTTP caching or managed CDNs. We present our protocol design along with a Linux-based implementation and some initial feasibility checks
Modeling Data-Plane Power Consumption of Future Internet Architectures
With current efforts to design Future Internet Architectures (FIAs), the
evaluation and comparison of different proposals is an interesting research
challenge. Previously, metrics such as bandwidth or latency have commonly been
used to compare FIAs to IP networks. We suggest the use of power consumption as
a metric to compare FIAs. While low power consumption is an important goal in
its own right (as lower energy use translates to smaller environmental impact
as well as lower operating costs), power consumption can also serve as a proxy
for other metrics such as bandwidth and processor load.
Lacking power consumption statistics about either commodity FIA routers or
widely deployed FIA testbeds, we propose models for power consumption of FIA
routers. Based on our models, we simulate scenarios for measuring power
consumption of content delivery in different FIAs. Specifically, we address two
questions: 1) which of the proposed FIA candidates achieves the lowest energy
footprint; and 2) which set of design choices yields a power-efficient network
architecture? Although the lack of real-world data makes numerous assumptions
necessary for our analysis, we explore the uncertainty of our calculations
through sensitivity analysis of input parameters
Stochastic Dynamic Cache Partitioning for Encrypted Content Delivery
In-network caching is an appealing solution to cope with the increasing
bandwidth demand of video, audio and data transfer over the Internet.
Nonetheless, an increasing share of content delivery services adopt encryption
through HTTPS, which is not compatible with traditional ISP-managed approaches
like transparent and proxy caching. This raises the need for solutions
involving both Internet Service Providers (ISP) and Content Providers (CP): by
design, the solution should preserve business-critical CP information (e.g.,
content popularity, user preferences) on the one hand, while allowing for a
deeper integration of caches in the ISP architecture (e.g., in 5G femto-cells)
on the other hand.
In this paper we address this issue by considering a content-oblivious
ISP-operated cache. The ISP allocates the cache storage to various content
providers so as to maximize the bandwidth savings provided by the cache: the
main novelty lies in the fact that, to protect business-critical information,
ISPs only need to measure the aggregated miss rates of the individual CPs and
do not need to be aware of the objects that are requested, as in classic
caching. We propose a cache allocation algorithm based on a perturbed
stochastic subgradient method, and prove that the algorithm converges close to
the allocation that maximizes the overall cache hit rate. We use extensive
simulations to validate the algorithm and to assess its convergence rate under
stationary and non-stationary content popularity. Our results (i) testify the
feasibility of content-oblivious caches and (ii) show that the proposed
algorithm can achieve within 10\% from the global optimum in our evaluation
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
Optimal Cache Allocation for Content-Centric Networking
This work was supported by the National Basic Research Program of China with Grant 2012CB315801, the National Natural Science Foundation of China (NSFC) with Grants 61133015 and 61272473, the National High-tech R&D Program of China with Grant 2013AA013501, and by the Strategic Priority Research Program of CAS with Grant X-DA06010303. The work was also supported by the EC EINS and EPSRC IU-ATC projects
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